Paper Digest: Recent Papers on Transformer
Paper Digest Team extracted all recent Transformer (NLP) related papers on our radar, and generated highlight sentences for them. The results are then sorted by relevance & date. In addition to this ‘static’ page, we also provide a real-time version of this article, which has more coverage and is updated in real time to include the most recent updates on this topic.
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TABLE 1: Paper Digest: Recent Papers on Transformer
| Paper | Author(s) | Source | Date | |
|---|---|---|---|---|
| 1 | Multimodal Hierarchical Transformer Enriched By Temporal Features and The CTC Loss Model: Depression Detection Model Based on Multimodal Hierarchical Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Save |
XIAOPING YUE et. al. | Biomed. Signal Process. Control. | |
| 2 | Using Transformer-based Models for Vietnamese Language Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper introduces a solution to the problem of detecting whether a sequence of text is Vietnamese based on its orthography and contextual features. |
Son Tran; Phuoc Tran; | PLOS One | 2026-02-13 |
| 3 | Data Security and Privacy in GPT Models: Techniques and Challenges Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents a systematic literature review conducted in accordance with the PRISMA 2020 guidelines, analyzing 60 peer-reviewed empirical studies published between 2020 and 2025 in Q1 and Q2 journals indexed in the Web of Science Core Collection. |
David Ghiurău; Daniela Elena Popescu; | Applied Sciences | 2026-02-13 |
| 4 | An Explainable Deep Learning Framework for Biosensing Data Interpretation in Biomedical Engineering and Real-time Health Diagnostics Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Introduction This work proposes an explainable deep learning framework to transform complex biosignal dynamics into interpretable health assessments. |
Zheng Yang; Weihong Huang; Heng Zhang; | Frontiers in Bioengineering and Biotechnology | 2026-02-12 |
| 5 | Hybrid Deep Learning–Geostatistical Mapping of Forest Aboveground Biomass in Lishui, China Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study proposes a hybrid framework that combines a CNN-Transformer (Convolutional Neural Network-Transformer) model with geostatistical Kriging of residuals to improve regional AGB mapping in Lishui City, Zhejiang Province, China. |
RUI QIAN et. al. | Plants | 2026-02-12 |
| 6 | Simplifying Radiology Reports with Large Language Models: Privacy-compliant Open- Versus Closed-weight Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study compares closed-weight and in-hospital deployed privacy-compliant open-weight LLMs in generating patient-friendly radiology reports. |
ANNEMARIE KATHARINA PROFF et. al. | European Radiology | 2026-02-12 |
| 7 | CONTEXT-AWARE SENTIMENT CLASSIFICATION OF SOCIAL MEDIA TEXT USING ATTENTION-BASED TRANSFORMER MODELS Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper proposes a Context-Aware Sentiment Classification Framework using attention-based transformer models to capture semantic relationships and contextual dependencies within social media text. |
Mr.M.N.Mallikarjuna Reddy; | American Journal of AI Cyber Computing Management | 2026-02-12 |
| 8 | Development of Retrieval-augmented Generation–based Large Language Model for Drug-induced Liver Injury Using Livertox Data Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We hypothesize that retrieval-augmented generation (RAG) integration—grounding LLM responses in LiverTox content—would enable accurate DILI decision support. |
ASHWIN RAO et. al. | Hepatology Communications | 2026-02-12 |
| 9 | Neutral Prompts, Non-Neutral People: Quantifying Gender and Skin-Tone Bias in Gemini Flash 2.5 Image and GPT Image 1.5 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The analysis employed a rigorous pipeline combining hybrid color normalization, facial landmark masking, and perceptually uniform skin tone quantification using the Monk (MST), PERLA, and Fitzpatrick scales. |
Roberto Balestri; | arxiv-cs.AI | 2026-02-12 |
| 10 | Beyond Generalist LLMs: Building and Validating Domain-specific Models with The SpAMCQA Benchmark Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Aim: General-purpose Large Language Models (LLMs) exhibit significant limitations in high-stakes clinical domains such as spondyloarthritis (SpA) diagnosis, yet the absence of specialized evaluation tools precludes the quantification of these failures. This study aims to break this critical evaluation impasse and rigorously test the hypothesis that domain specialization is a necessity for achieving expert-level performance in complex medical diagnostics. |
XIAOJIAN JI et. al. | Artificial Intelligence Surgery | 2026-02-12 |
| 11 | Extending Puzzle for Mixture-of-Experts Reasoning Models with Application to GPT-OSS Acceleration Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We extend and apply Puzzle, a post-training neural architecture search (NAS) framework, to gpt-oss-120B to produce gpt-oss-puzzle-88B, a deployment-optimized derivative. |
AKHIAD BERCOVICH et. al. | arxiv-cs.LG | 2026-02-12 |
| 12 | CLAS-Net: A Study on Cross-lingual Intelligent Sentiment Analysis Model Fusing Semantic Alignment Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study proposes a novel cross-lingual sentiment analysis framework, CLAS-Net, designed to address the bottlenecks of current public opinion analysis systems in multilingual scenarios. |
Jia-Qi Wang; | PLOS One | 2026-02-11 |
| 13 | Compiler-Guided Inference-Time Adaptation: Improving GPT-5 Programming Performance in Idris Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This work investigates whether GPT-5 can effectively acquire proficiency in an unfamiliar functional programming language, Idris, through iterative, feedback driven prompting. |
Minda Li; Bhaskar Krishnamachari; | arxiv-cs.PL | 2026-02-11 |
| 14 | Step-resolved Data Attribution for Looped Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To make SDI practical at transformer scale, we propose a TensorSketch implementation that never materialises per-example gradients. |
Georgios Kaissis; David Mildenberger; Juan Felipe Gomez; Martin J. Menten; Eleni Triantafillou; | arxiv-cs.LG | 2026-02-10 |
| 15 | Training Objectives and Evaluation Metrics for Counterfactual Story Rewriting Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Analogously, standard evaluation metrics that weigh all tokens equally may not be able to discriminate effectively between more correct and less correct predictions. For these reasons, in this paper we propose novel training objectives and evaluation metrics that mirror this task more closely, and train and evaluate two Flan-T5 transformer models accordingly. |
Amelie Girard; Inigo Jauregi Unanue; Massimo Piccardi; | ACM Transactions on Asian and Low-Resource Language … | 2026-02-10 |
| 16 | LLMs As Hackers: Autonomous Linux Privilege Escalation Attacks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: However, a comprehensive understanding of LLMs’ efficacy and limitations in performing autonomous Linux privilege-escalation attacks remains underexplored. To address this gap, we introduce hackingBuddyGPT , a fully automated LLM-driven prototype designed for evaluating autonomous Linux privilege-escalation. |
Andreas Happe; Aaron Kaplan; Jürgen Cito; | Empirical Software Engineering | 2026-02-10 |
| 17 | A Small-Scale System for Autoregressive Program Synthesis Enabling Controlled Experimentation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present a system called Cadmus which includes an integer virtual machine (VM), a dataset composed of true programs of diverse tasks, and an autoregressive transformer model that is trained for under \$200 of compute cost. |
Russ Webb; Jason Ramapuram; | arxiv-cs.AI | 2026-02-09 |
| 18 | LLM-IARE: An Input-Aware Resilience Estimation Methodology for LLMs Under Hardware Transient Faults Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Traditional Fault Injection (FI) approaches are time consuming due to a large number of repeated executions, which limits their scalability to fast evaluate large-scale resilience. To address these challenges, we propose LLM-IARE, a novel Input-Aware Resilience Estimation Model for LLMs under hardware transient faults. |
Jiajia Jiao; Tainian Zhou; Ran Wen; Yulian Li; Jin Liu; | ACM Transactions on Design Automation of Electronic Systems | 2026-02-09 |
| 19 | Bielik Guard: Efficient Polish Language Safety Classifiers for LLM Content Moderation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: As Large Language Models (LLMs) become increasingly deployed in Polish language applications, the need for efficient and accurate content safety classifiers has become paramount. We present Bielik Guard, a family of compact Polish language safety classifiers comprising two model variants: a 0.1B parameter model based on MMLW-RoBERTa-base and a 0.5B parameter model based on PKOBP/polish-roberta-8k. Fine-tuned on a community-annotated dataset of 6,885 Polish texts, these models classify content across five safety categories: Hate/Aggression, Vulgarities, Sexual Content, Crime, and Self-Harm. |
Krzysztof Wróbel; Jan Maria Kowalski; Jerzy Surma; Igor Ciuciura; Maciej Szymański; | arxiv-cs.CL | 2026-02-08 |
| 20 | GenAI-supported Portfolio Assessment for Complex Thinking: A GPT-based Innovation in Business Education Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Conducted at a graduate business school in Peru with 120 student portfolios, the research adopted a qualitative exploratory-documentary approach, complemented by a correlational analysis between human and AI evaluations to enhance the interpretive validity of the findings. |
May Portuguez-Castro; Isolda Margarita Castillo-Martínez; | Frontiers in Education | 2026-02-06 |
| 21 | Evaluating The Role of ChatGPT in Structured Radiology Reporting: A Systematic Review Related Papers Related Patents Related Grants Related Venues Related Experts View Save |
SHAHAD ALALAWI et. al. | Medicine | 2026-02-06 |
| 22 | Deep Research Capabilities in GPT‐5 Thinking and Gemini 2.5 Pro Improve Citation Integrity and Concordance with American Academy of Orthopaedic Surgeons Anterior Cruciate Ligament and Rotator Cuff Guidelines Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Abstract Purpose To assess whether large language models (LLMs) with advanced reasoning and live web search (LWS) provide recommendations concordant with evidence‐based clinical practice guidelines (CPGs) developed by the American Academy of Orthopaedic Surgeons (AAOS) for anterior cruciate ligament (ACL) and rotator cuff (RC) injury management. |
Hilmi Burak Şengül; Barış Akın; Mahmut Enes Kayaalp; Erdem Aras Sezgin; | Knee Surgery, Sports Traumatology, Arthroscopy | 2026-02-06 |
| 23 | Automated Radiological Report Generation from Breast Ultrasound Images Using Vision and Language Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we propose a multimodal Transformer-based framework for automatic breast ultrasound report generation that integrates visual and textual information through cross-attention mechanisms. |
Shaheen Khatoon; Azhar Mahmood; | Journal of Imaging | 2026-02-06 |
| 24 | Emulating Aggregate Human Choice Behavior and Biases with GPT Conversational Agents Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We adapted three well-established decision scenarios into a conversational setting and conducted a human experiment (N=1100). |
Stephen Pilli; Vivek Nallur; | arxiv-cs.AI | 2026-02-05 |
| 25 | DARWIN: Dynamic Agentically Rewriting Self-Improving Network Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: DARWIN is an evolutionary GPT model, utilizing a genetic-algorithm like optimization structure with several independent GPT agents being trained individually using unique training … |
Henry Jiang; | arxiv-cs.NE | 2026-02-05 |
| 26 | Explainable Turkish E-Commerce Review Classification Using A Multi-Transformer Fusion Framework and SHAP Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study aims to classify Turkish e-commerce reviews as either useful or useless, thereby highlighting high-quality content to support more informed consumer decisions. |
Sıla Çetin; Esin Ayşe Zaimoğlu; | Journal of Theoretical and Applied Electronic Commerce … | 2026-02-05 |
| 27 | Does ChatGPT Enhance Equity for Global Health Publications? Copyediting By ChatGPT Compared to Grammarly and A Human Editor Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In a preliminary, in-depth case comparison, we compared the number and quality of corrections made by U-M GPT, a secure, University of Michigan-hosted generative AI tool, to those from Grammarly and a human editor to text from two draft papers written by Ugandan sexual and reproductive health researchers. |
ELLA AUGUST et. al. | PLOS One | 2026-02-05 |
| 28 | T-LSTM: A Novel Model for High-Precision Wind Power Prediction By Integrating Transformer and Improved LSTM Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, existing wind power prediction models face three key challenges: traditional long short-term memory (LSTM) models struggle to capture long-term temporal dependencies efficiently and have high training latency, while Transformer-based models exhibit excessive computational complexity and are prone to overfitting for short-term fluctuating data; meanwhile, few models integrate seasonal trend modeling with multi-scale temporal feature extraction, leading to large prediction errors in seasonal transitions. To address these issues, this paper proposes a hybrid prediction framework combining a novel T-LSTM recurrent unit with the Seasonal Autoregressive Integrated Moving Average (SARIMA) model. |
Qin Zhong; Long Wang; Chao Huang; | Applied Sciences | 2026-02-05 |
| 29 | Parity, Sensitivity, and Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We give a new construction of a transformer for PARITY with softmax, length-independent and polynomially bounded positional encoding, no layernorm, working both with and without causal masking. |
Alexander Kozachinskiy; Tomasz Steifer; Przemysław Wałȩga; | arxiv-cs.LG | 2026-02-05 |
| 30 | Using Large Language Models to Complement Humans for The Coding of Social Media Interactions Between Science Teachers Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study proposes several possible strategies for the integration of LLMs into qualitative coding workflows, as well as offering suggestions to improve LLM performance through prompt engineering. |
Robertson Burgess; Katie Waters; Erika Spray; Elena Prieto-Rodriguez; | Discover Education | 2026-02-04 |
| 31 | Greedy-Gnorm: A Gradient Matrix Norm-Based Alternative to Attention Entropy for Head Pruning Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose Greedy-Gradient norm (Greedy-Gnorm), a novel head pruning algorithm that dynamically recalculates head importance after each pruning step. |
Yuxi Guo; Paul Sheridan; | arxiv-cs.LG | 2026-02-04 |
| 32 | Can LLMs Capture Stable Human-generated Sentence Entropy Measures? Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Here, we address both issues using two large publicly available cloze datasets in German 1 and English 2. |
Estrella Pivel-Villanueva; Elisabeth Frederike Sterner; Franziska Knolle; | arxiv-cs.CL | 2026-02-04 |
| 33 | Alignment Drift in Multimodal LLMs: A Two-Phase, Longitudinal Evaluation of Harm Across Eight Model Releases Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present a two-phase evaluation of MLLM harmlessness using a fixed benchmark of 726 adversarial prompts authored by 26 professional red teamers. |
Casey Ford; Madison Van Doren; Emily Dix; | arxiv-cs.CL | 2026-02-04 |
| 34 | An Efficient Multi‐Physics GPT‐PINN Framework for Predicting Reactive Solute Transport in Parameterized Groundwater Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Abstract Modeling coupled groundwater flow and reactive transport for multi‐query tasks is computationally prohibitive, and standard Physics‐Informed Neural Networks (PINNs) require costly retraining for each new parameter. We introduce the Multi‐Physics Generative Pre‐trained PINN (MP‐GPT‐PINN), a meta‐learning framework to resolve this bottleneck. |
ZHIYU JIAO et. al. | Geophysical Research Letters | 2026-02-04 |
| 35 | GenAI Agent for Automated Analysis and Personalization of Drug Prevention Campaigns Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study introduces a generative artificial intelligence (GenAI) agent designed to autonomously evaluate, optimize, and personalize drug prevention campaigns across Facebook, Reddit, Instagram, and Twitter (X) using a 45,000-post multi-platform awareness corpus. |
Mohammed Aljaafari; Shaymaa Sorour; | Scientific Journal of King Faisal University Humanities and … | 2026-02-03 |
| 36 | SOGPTSpotter: Detecting ChatGPT-Generated Answers on Stack Overflow Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce a novel approach, SOGPTSpotter, that employs Siamese Neural Networks, leveraging the BigBird model and the Triplet loss, to detect ChatGPT-generated answers on Stack Overflow. |
Suyu Ma; Chunyang Chen; Hourieh Khalajzadeh; John Grundy; | arxiv-cs.SE | 2026-02-03 |
| 37 | A Comparative Evaluation of Large Language Models for Simplifying Prostate Cancer Pathology Reports: ChatGPT and Gemini Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Their application shows potential to enhance patient comprehension and clinical communication. |
HAOYANG ZENG et. al. | International Journal of Surgery | 2026-02-03 |
| 38 | A Novel Dual-Layer Deep Learning Architecture for Phishing and Spam Email Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study proposes a dual-layer deep learning architecture designed to enhance email security by improving the detection of phishing and spam messages. |
Sarmad Rashed; Caner Ozcan; | Electronics | 2026-02-02 |
| 39 | Assessing Large Language Models As Assistive Tools in Selecting First Trial Lens Parameters for Orthokeratology Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study aims to evaluate the performance of LLMs as assistive tools in the CRT-related orthokeratology fitting workflow. |
YIJIN HAN et. al. | Frontiers in Medicine | 2026-02-02 |
| 40 | UAT-LITE: Inference-Time Uncertainty-Aware Attention for Pretrained Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose UAT-LITE, an inference-time framework that makes self-attention uncertainty-aware using approximate Bayesian inference via Monte Carlo dropout in pretrained transformer classifiers. |
ELIAS HOSSAIN et. al. | arxiv-cs.AI | 2026-02-02 |
| 41 | MBTI Personality Prediction Using GPT-2 LLM Augmentation and Ensemble Machine Learning Approaches Related Papers Related Patents Related Grants Related Venues Related Experts View Save |
Devraj Patel; Sunita V. Dhavale; | Multimedia Tools and Applications | 2026-02-01 |
| 42 | Semi-supervised CAPP Transformer Learning Via Pseudo-labeling Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose a semi-supervised learning approach to improve transformer-based CAPP transformer models without manual labeling. |
DENNIS GROSS et. al. | arxiv-cs.LG | 2026-02-01 |
| 43 | SimpleGPT: Improving GPT Via A Simple Normalization Strategy Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we revisit Transformer optimization through the lens of second-order geometry and establish a direct connection between architectural design, activation scale, the Hessian matrix, and the maximum tolerable learning rate. |
Marco Chen; Xianbiao Qi; Yelin He; Jiaquan Ye; Rong Xiao; | arxiv-cs.LG | 2026-02-01 |
| 44 | MAU-GPT: Enhancing Multi-type Industrial Anomaly Understanding Via Anomaly-aware and Generalist Experts Adaptation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, existing approaches are hindered by limited dataset coverage and poor model generalization across diverse and complex anomaly patterns. To address these challenges, we introduce MAU-Set, a comprehensive dataset for Multi-type industrial Anomaly Understanding. |
ZHUONAN WANG et. al. | arxiv-cs.CV | 2026-01-31 |
| 45 | Transformer-Based Model for Multilingual Hope Speech Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work various transformers have been implemented and evaluated for hope speech detection for English and Germany. |
Nsrin Ashraf; Mariam Labib; Hamada Nayel; | arxiv-cs.CL | 2026-01-31 |
| 46 | Artificial Intelligence Breakthroughs and Data Futures: A Retrospective and Prospective Review Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents a comprehensive synthesis of major breakthroughs in artificial intelligence (AI) over the past fifteen years, integrating historical, theoretical, and technological perspectives. |
Beyazıt Bestami Yüksel; Ayşe Yılmazer Metin; | Academic Platform Journal of Engineering and Smart Systems | 2026-01-31 |
| 47 | Robust and Multicenter Detection of Breast Malignancies Using Vision Transformers in Digital Breast Tomosynthesis Imaging Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This framework focuses on image‐level classification of normal, benign, and malignant cases, rather than lesion‐level detection, utilizing DBT images to enhance accuracy and generalizability. |
AMIT SHARMA et. al. | International Journal of Imaging Systems and Technology | 2026-01-30 |
| 48 | Brazilian Portuguese Image Captioning with Transformers: A Study on Cross-Native-Translated Dataset Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We use a version of Flickr30K comprised of captions manually created by native Brazilian Portuguese speakers and compare it to a version with captions automatically translated from English to Portuguese. |
Gabriel Bromonschenkel; Alessandro L. Koerich; Thiago M. Paixão; Hilário Tomaz Alves de Oliveira; | arxiv-cs.CV | 2026-01-30 |
| 49 | Hierarchical Shift Mixing — Beyond Dense Attention in Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Attempts have been made to replace it with less complex methods, at the cost of reduced performance in most cases. We introduce Hierarchical Shift Mixing (HSM), a general framework for token mixing that distributes pairwise token interactions across Transformer layers rather than computing them densely within each layer. |
Robert Forchheimer; | arxiv-cs.LG | 2026-01-30 |
| 50 | YuriiFormer: A Suite of Nesterov-Accelerated Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose a variational framework that interprets transformer layers as iterations of an optimization algorithm acting on token embeddings. |
Aleksandr Zimin; Yury Polyanskiy; Philippe Rigollet; | arxiv-cs.LG | 2026-01-30 |
| 51 | Advanced of LLM Transformers and Zero-shot XGBoost for Accurate Arabic Text Insights and Profit Predictions Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Abstract This research proposes an innovative Arabic financial forecasting model that integrates linguistic relation extraction with advanced deep learning and machine learning techniques. |
Sally Mohamed Ali Elmorsy; | Journal of Electrical Systems and Information Technology | 2026-01-30 |
| 52 | MiNER: A Two-Stage Pipeline for Metadata Extraction from Municipal Meeting Minutes Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we propose a two-stage pipeline for metadata extraction from municipal minutes. |
RODRIGO BATISTA et. al. | arxiv-cs.CL | 2026-01-30 |
| 53 | Quantifying Model Uniqueness in Heterogeneous AI Ecosystems Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Here, we introduce a statistical framework for auditing model uniqueness based on In-Silico Quasi-Experimental Design (ISQED). |
Lei You; | arxiv-cs.AI | 2026-01-30 |
| 54 | Tell Me What I Missed: Tell Me What I Missed: Interacting with GPT During Recalling of One-Time Witnessed Events Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We studied participants who watched a short robbery video (approximating a one-time eyewitness scenario) and composed recall statements using either a default GPT or a guided GPT prompted with a standardized eyewitness protocol. |
Suifang Zhou; Qi Gong; Ximing Shen; RAY LC; | arxiv-cs.HC | 2026-01-29 |
| 55 | From ChatGPT to UroGPT: A Guideline-trained Artificial Intelligence Model for Male Infertility Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We posed 25 clinical questions derived from the Male Infertility Guidelines and expert opinions to both the standard ChatGPT (GPT-4o) and UroGPT. |
ELIE KAPLAN-MARANS et. al. | Current Urology | 2026-01-29 |
| 56 | CoFrGeNet: Continued Fraction Architectures for Language Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, inspired by continued fractions, we introduce a new function class for generative modeling. |
AMIT DHURANDHAR et. al. | arxiv-cs.CL | 2026-01-29 |
| 57 | Metadata Driven Malicious URL Detection Using RoBERTa Large and Multi Source Network Threat Intelligence Related Papers Related Patents Related Grants Related Venues Related Experts View Save |
Lina Chen; Liang Meng; | Scientific Reports | 2026-01-29 |
| 58 | Private Speech: Similarities Between A Large Language Model and Children Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In an exploratory serial recall study, we tasked GPT-3.5-Turbo-instruct and observed incidental private speech, indicating that the phenomenon extends across contexts. |
Zhiyu Liang; Leon On Tay; Simon Dennis; | Frontiers in Artificial Intelligence | 2026-01-29 |
| 59 | Depression Detection on Social Media Using Multi-Task Learning with BERT and Hierarchical Attention: A DSM-5-Guided Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose a DSM-5-guided methodology that systematically maps clinical diagnostic criteria to computable social media features across three modalities: textual semantics (BERT-based deep semantic extraction), behavioral patterns (temporal activity analysis), and topic distributions (LDA-based cognitive bias identification). |
Haichao Jin; Lin Zhang; | Electronics | 2026-01-29 |
| 60 | Abstract DP042: Explainable Natural Language Processing (NLP) Models to Predict 90-day Mortality of Different Stroke Types from Clinical Note Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Methods: We used the Medical Information Mart for Intensive Care (MIMIC-IV) database (>40,000 ICU patients; Beth Israel Deaconess Medical Center, 2008–2019) and identified 7,511 patients with acute ischemic stroke, spontaneous intracerebral hemorrhage (ICH), non-traumatic subarachnoid hemorrhage (SAH), and traumatic SAH. |
ANH TUAN TRAN et. al. | Stroke | 2026-01-29 |
| 61 | From Generative Modeling to Clinical Classification: A GPT-Based Architecture for EHR Notes Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study presents a GPT-based architecture for clinical text classification that adapts a pretrained decoder-only Transformer using a selective fine-tuning strategy. |
Fariba Afrin Irany; | arxiv-cs.CL | 2026-01-29 |
| 62 | LAMP: Look-Ahead Mixed-Precision Inference of Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Based on the rounding error analysis of a composition $f(g(\mathrm{x}))$, we provide an adaptive strategy that selects a small subset of components of $g(\mathrm{x})$ to be computed more accurately while all other computations can be carried out with lower accuracy. |
STANISLAV BUDZINSKIY et. al. | arxiv-cs.LG | 2026-01-29 |
| 63 | Detecting AI-generated Text in High-resource Languages: Developing A RoBERTa-CNN Hybrid Model for Academic Integrity Challenge Related Papers Related Patents Related Grants Related Venues Related Experts View Save |
Manish Prajapati; Santos Kumar Baliarsingh; Prabhu Prasad Dev; | International Journal of Machine Learning and Cybernetics | 2026-01-29 |
| 64 | Influence of Solution Efficiency and Valence of Instruction on Additive and Subtractive Solution Strategies in Humans, GPT-4, and GPT-4o Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Study 1 comprised four experiments (1a, 1b, 2a, 2b) with 588 human participants and 680 GPT-4 outputs; Study 2 included two experiments (3a, 3b) with 751 human participants and 1,080 GPT-4o outputs. |
Lydia Uhler; Verena Jordan; Jürgen Buder; Markus Huff; Frank Papenmeier; | Communications Psychology | 2026-01-28 |
| 65 | Structurally Human, Semantically Biased: Detecting LLM-Generated References with Embeddings and GNNs Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We show the robustness of our findings by replicating the pipeline with Claude Sonnet 4.5 and with multiple embedding models (OpenAI and SPECTER), with RF separability for ground truth vs.\ Claude $\approx 0.77$ and clean rejection of the random baseline. |
Melika Mobini; Vincent Holst; Floriano Tori; Andres Algaba; Vincent Ginis; | arxiv-cs.LG | 2026-01-28 |
| 66 | Large Language Models Naively Recover Ethnicity from Individual Records Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: I demonstrate that large language models can infer ethnicity from names with accuracy exceeding that of Bayesian Improved Surname Geocoding (BISG) without additional training data, enabling inference outside the United States and to contextually appropriate classification categories. |
Noah Dasanaike; | arxiv-cs.CL | 2026-01-28 |
| 67 | LLM4ATS: Applying Large Language Models for Auto-Testing Scripts in Automobiles Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper introduces LLM4ATS, a framework integrating large language models, RAG, and closed-loop verification to automatically generate highly reliable automotive automated test scripts from natural language descriptions. |
Zeyuan Li; Wei Li; Yuezhao Liu; Wenhao Li; Min Chen; | Big Data and Cognitive Computing | 2026-01-28 |
| 68 | Strategic Energy Project Investment Decisions Using RoBERTa: A Framework for Efficient Infrastructure Evaluation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study investigates the application of the robustly optimized BERT model (RoBERTa) for identifying high-value energy infrastructure projects. |
Recep Özkan; Fatemeh Mostofi; Fethi Kadıoğlu; Vedat Toğan; Onur Behzat Tokdemir; | Buildings | 2026-01-28 |
| 69 | Investigating Transformer Models for Textual Bias Detection in Model, Data, and Dataspace Cards Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Partial fine-tuning (zero-shot) evaluations of models trained only on BABE or synthetic data revealed substantial performance drops on this real-world set. To mitigate this cross-domain loss, we introduce a cascaded, full fine-tuning (few-shot) pipeline in which Transformer models are sequentially fine-tuned on BABE, synthetic text, and a subset of the Hugging Face corpus. |
ANDY DONALD et. al. | AI and Ethics | 2026-01-28 |
| 70 | In-Context Reinforcement Learning From Suboptimal Historical Data Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this case, standard autoregressive training corresponds to imitation learning and results in suboptimal performance. To address this, we propose the Decision Importance Transformer(DIT) framework, which emulates the actor-critic algorithm in an in-context manner. |
Juncheng Dong; Moyang Guo; Ethan X. Fang; Zhuoran Yang; Vahid Tarokh; | arxiv-cs.LG | 2026-01-27 |
| 71 | Transformer-Based Hate Speech Detection in Online Content Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This research demonstrates the efficiency of deep learning in detecting hate speech and underscores the need for continued study in order to create fair, reliable, and flexible detection systems. |
P B Jishnu; C Vishnu Mohan; | International Research Journal on Advanced Engineering Hub … | 2026-01-27 |
| 72 | Harnessing Multimodal Large Language Models to Interpret Ecological Momentary Assessment-generated Caregiving Photographs Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Abstract Multimodal large language models (MLLMs) are rapidly advancing tools capable of synthesizing text and image data, and their potential application with patient- and caregiver-generated health data is gaining increasing attention. |
Christy Muasher-Kerwin; M. Courtney Hughes; Aida Sanatizadeh; Jamie F. Mayer; Hamed Alhoori; | Discover Artificial Intelligence | 2026-01-27 |
| 73 | Rethinking Intelligence: Brain-like Neuron Network Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: From the perspective of neuroscience, we rethink the formation and evolution of intelligence and proposes a new neural network paradigm, Brain-like Neural Network (BNN). |
Weifeng Liu; | arxiv-cs.NE | 2026-01-27 |
| 74 | A GPT-reinforced Social Robot for Patient Communication: A Pilot Study Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The aim of this study is to develop and test the feasibility of using a social robot that can convincingly provide health information in patient dialogues within clinical practice, to support patient communication and information exchange. |
JAN-WILLEM J. R. VAN ‘T KLOOSTER et. al. | Frontiers in Digital Health | 2026-01-27 |
| 75 | Large Language Models for Agricultural and Rural Development: An Application of Foundational Models in Extension Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study investigates the applicability, practicality, and effectiveness of a low-cost AI foundational model (FM) in agricultural extension through the development, fine-tuning, and evaluation of a custom GPT named Utah PeachBot, built using OpenAI’s GPT platform. |
Paul A. Hill; Lendel K. Narine; | Advancements in Agricultural Development | 2026-01-26 |
| 76 | Fine-Grained Emotion Detection on GoEmotions: Experimental Comparison of Classical Machine Learning, BiLSTM, and Transformer Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we benchmark three modeling families on the GoEmotions dataset: a TF-IDF-based logistic regression system trained with binary relevance, a BiLSTM with attention, and a BERT model fine-tuned for multi-label classification. |
Ani Harutyunyan; Sachin Kumar; | arxiv-cs.CL | 2026-01-26 |
| 77 | Capsule-enhanced RoBERTa for Hierarchical Sentiment Analysis on Social Media Texts IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save |
Ritu Gauraha; Ayush Kumar Agrawal; Parul Dubey; | Discover Artificial Intelligence | 2026-01-25 |
| 78 | Prompt Injection Evaluations: Refusal Boundary Instability and Artifact-Dependent Compliance in GPT-4-Series Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We evaluated two models, GPT-4.1 and GPT-4o, using 3,274 perturbation runs derived from refusal-inducing prompt injection attempts. |
Thomas Heverin; | arxiv-cs.CR | 2026-01-25 |
| 79 | Sentiment Analysis in Social Networks: A Case Study on Student Feedback Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Methods: This study uses several sentiment analysis approaches, including Support Vector Machine (SVM) along with TF-IDF features, Long Short-Term Memory (LSTM) networks, a hybrid TF-IDF–LSTM model, and transformer-based models like BERT and RoBERTa. |
Manoj Kumar Srivastav; Somsubhra Gupta; | Indian Journal Of Science And Technology | 2026-01-24 |
| 80 | Seq2Turk: Turkish Spelling Error Correction Using Context-Dependent Sequence-to-Sequence Model Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this study, we propose a context-dependent spelling correction model for Turkish, which is an agglutinative language with a rich morphology and a complex grammatical structure. |
Burak Aytan; C. Okan Sakar; | ACM Transactions on Asian and Low-Resource Language … | 2026-01-24 |
| 81 | Survey on Fake News Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we explore and compare multiple approaches for fake news detection using a common dataset. |
Soham Sathe, Amaan Shaikh, Sahil Shrotri; A. A. Chandorkar Vaishnavi Thakur; | International Journal of Advanced Research in Science … | 2026-01-24 |
| 82 | Limitations in Chest X-Ray Interpretation By Vision-Capable Large Language Models, Gemini 1.0, Gemini 1.5 Pro, GPT-4 Turbo, and GPT-4o Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Primary diagnosis accuracy was assessed based on whether the model correctly identified the target diagnostic category and was classified as fully correct, partially correct, or incorrect according to predefined clinical criteria. |
Chih-Hsiung Chen; Chang-Wei Chen; Kuang-Yu Hsieh; Kuo-En Huang; Hsien-Yung Lai; | Diagnostics | 2026-01-23 |
| 83 | Research on The State of Charge Estimation of Electric Forklift Batteries Based on An Improved Transformer Model Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The mean absolute error (MAE) and root mean square error (RMSE) of the improved Transformer model obtained using the Kalman filter – PCA method are reduced by 26.32% and 27.73% respectively, compared to the single Kalman method. |
Jia Wang; Shenglong Zhang; Xia Hu; | Batteries | 2026-01-23 |
| 84 | Improving Hate Speech Detection with Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this study, we fine-tuned GPT-4o-mini using a unique corpus of online comments annotated by diverse groups of coders with varying annotation quality: research assistants, activists, two kinds of crowd workers, and citizen scientists. |
NATALIA UMANSKY et. al. | European Journal of Political Research | 2026-01-23 |
| 85 | Comparative Analysis of Multimodal Large Language Models GPT-4o and O1 Versus Clinicians in Clinical Case Challenge Questions: Retrospective Cross-sectional Study Related Papers Related Patents Related Grants Related Venues Related Experts View Save |
Jaewon Jung; Hyunjae Kim; SungA Bae; Jin Young Park; | Medicine | 2026-01-23 |
| 86 | Regional Bias in Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce FAZE, a prompt-based evaluation framework that measures regional bias on a 10-point scale, where higher scores indicate a stronger tendency to favor specific regions. |
M P V S Gopinadh; Kappara Lakshmi Sindhu; Soma Sekhar Pandu Ranga Raju P; Yesaswini Swarna; | arxiv-cs.CL | 2026-01-22 |
| 87 | Even GPT-5.2 Can’t Count to Five: The Case for Zero-Error Horizons in Trustworthy LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose Zero-Error Horizon (ZEH) for trustworthy LLMs, which represents the maximum range that a model can solve without any errors. |
Ryoma Sato; | arxiv-cs.LG | 2026-01-22 |
| 88 | Zero-Shot Product Attribute Labeling with Vision-Language Models: A Three-Tier Evaluation Framework Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This requires models to detect attribute applicability before attempting classification. We introduce a three-tier evaluation framework that decomposes this challenge: (1) overall task performance across all classes (including NA class: suggesting attribute is not applicable) for all attributes, (2) attribute applicability detection, and (3) fine-grained classification when attributes are determinable. |
Shubham Shukla; Kunal Sonalkar; | arxiv-cs.CV | 2026-01-22 |
| 89 | Performance of DeepSeek and ChatGPT on The Chinese Health Professional and Technical Examination: A Comparative Study Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Background Large language models (LLMs) are increasingly applied in medical education, yet their reliability in specialized, high-stakes assessments such as the Chinese Health … |
XU LI et. al. | PLOS One | 2026-01-22 |
| 90 | Comparative Study of Large Language Models on Chinese Film Script Continuation: An Empirical Analysis Based on GPT-5.2 and Qwen-Max Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study provides a reproducible framework for LLM evaluation in Chinese creative writing. |
Yuxuan Cao; Zida Yang; Ye Wang; | arxiv-cs.CL | 2026-01-21 |
| 91 | Large Language Models and Conditional Rules in Clinical Decision Support Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Future work can explore integrating LLMs and LRMs with decision trees to improve effectiveness. |
SHANGEETHA SIVASOTHY et. al. | Health Information Science and Systems | 2026-01-21 |
| 92 | A Multimodal Ensemble-Based Framework for Detecting Fake News Using Visual and Textual Features Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To enhance accuracy in fake news detection, this article introduces an ensemble-based framework that integrates textual and visual data using ViLBERT’s two-stream architecture, incorporates VADER sentiment analysis to detect emotional language, and uses Image–Text Contextual Similarity to identify mismatches between visual and textual elements. |
MUHAMMAD ABDULLAH et. al. | Mathematics | 2026-01-21 |
| 93 | Large Language Models in Radiologic Numerical Tasks: A Thorough Evaluation and Error Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Abstract The purpose of this study was to investigate the performance of LLMs in radiology numerical tasks and perform a comprehensive error analysis. |
ALI NOWROOZI et. al. | Journal of Imaging Informatics in Medicine | 2026-01-21 |
| 94 | TrackletGPT: A Language-like GPT Framework for White Matter Tract Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This task remains complex, as tracts differ among themselves, across subjects and conditions, yet have similar 3D structure across hemispheres and subjects. To address these challenges, we propose TrackletGPT, a language-like GPT framework which reintroduces sequential information in tokens using tracklets. |
ANOUSHKRIT GOEL et. al. | arxiv-cs.CV | 2026-01-20 |
| 95 | Language, Caste, and Context: Demographic Disparities in AI-Generated Explanations Across Indian and American STEM Educational Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We conduct one of the first large-scale intersectional analyses on LLM explanation quality for Indian and American undergraduate profiles preparing for engineering entrance examinations. By constructing profiles combining multiple demographic dimensions including caste, medium of instruction, and school boards in India, and race, HBCU attendance, and school type in America, alongside universal factors like income and college tier, we examine how quality varies across these factors. |
Amogh Gupta; Niharika Patil; Sourojit Ghosh; S Gaikwad; | arxiv-cs.CY | 2026-01-20 |
| 96 | TransMode-LLM: Feature-Informed Natural Language Modeling with Domain-Enhanced Prompting for Travel Behavior Modeling Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study proposes TransMode-LLM, an innovative framework that integrates statistical methods with LLM-based techniques to predict travel modes from travel survey data. |
Meijing Zhang; Ying Xu; | arxiv-cs.CE | 2026-01-20 |
| 97 | Leveraging DistilBERT-Multilingual for Robust and Efficient AI-Based Fake News Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this research, a machine learning–based framework for fake news detection using the DistilBERT-base-multilingual-cased Transformer model is proposed. |
Arpita Kulkarni; Vaishnavi Pawade; Shilpa Mangshetty; | International Research Journal on Advanced Engineering Hub … | 2026-01-20 |
| 98 | Forma Mentis Networks Predict Creativity Ratings of Short Texts Via Interpretable Artificial Intelligence in Human and AI-simulated Raters Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We use textual forma mentis networks (TFMN) to extract network (semantic/syntactic associations) and emotional features from approximately one thousand human-, GPT3.5-, and Sonnet 3.7-generated stories. |
Edith Haim; Natalie Fischer; Salvatore Citraro; Giulio Rossetti; Massimo Stella; | Journal of Computational Social Science | 2026-01-20 |
| 99 | LLMOrbit: A Circular Taxonomy of Large Language Models -From Scaling Walls to Agentic AI Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present LLMOrbit, a comprehensive circular taxonomy navigating the landscape of large language models spanning 2019-2025. |
Badri N. Patro; Vijay S. Agneeswaran; | arxiv-cs.LG | 2026-01-20 |
| 100 | Integrating Large Language Models (LLMs) Into Neuro-oncologic Radiology: A Retrospective Feasibility Assessment of GPT-4o for Brain Tumor Diagnosis Related Papers Related Patents Related Grants Related Venues Related Experts View Save |
PEIWEN SUN et. al. | Neuroradiology | 2026-01-19 |
| 101 | METIS: Mentoring Engine for Thoughtful Inquiry & Solutions Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We ask whether an AI mentor can move undergraduates from an idea to a paper. |
Abhinav Rajeev Kumar; Dhruv Trehan; Paras Chopra; | arxiv-cs.LG | 2026-01-19 |
| 102 | Early Prediction of Type 2 Diabetes Using Multimodal Data and Tabular Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study introduces a novel approach for early Type 2 Diabetes Mellitus (T2DM) risk prediction using a tabular transformer (TabTrans) architecture to analyze longitudinal patient data. |
Sulaiman Khan; Md. Rafiul Biswas; Zubair Shah; | arxiv-cs.CV | 2026-01-19 |
| 103 | From Human to Machine Refactoring: Assessing GPT-4’s Impact on Python Class Quality and Readability Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we present a comprehensive empirical study on LLM-driven refactoring using GPT-4o, applied to 100 Python classes from the ClassEval benchmark. |
Alessandro Midolo; Emiliano Tramontana; Massimiliano Di Penta; | arxiv-cs.SE | 2026-01-19 |
| 104 | Neural Organ Transplantation (NOT): Checkpoint-Based Modular Adaptation for Transformer Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce Neural Organ Transplantation (NOT), a modular adaptation framework that enables trained transformer layers to function as reusable transferable checkpoints for domain adaptation. |
Ahmad Al-Zuraiqi; | arxiv-cs.LG | 2026-01-19 |
| 105 | Vision Language Models for Optimization-Driven Intent Processing in Autonomous Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present IntentOpt, a benchmark of 85 optimization problems across 17 categories, evaluating four VLMs (GPT-5-Mini, Claude-Haiku-4.5, Gemini-2.5-Flash, Llama-3.2-11B-Vision) under three prompting strategies on multimodal versus text-only inputs. |
Tasnim Ahmed; Yifan Zhu; Salimur Choudhury; | arxiv-cs.AI | 2026-01-19 |
| 106 | Hate Speech Detection in Nepali Social Media: A Comparative Analysis of Machine Learning and Transformer-based Approaches Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study demonstrates that lexicon-enhanced featureengineering significantly improves hate speech detection in lowresourcelanguages and provides practical recommendationsfor developing content moderation systems for Nepali-speakingcommunities. |
Palisha Shakya; Suraj Chand; Lalit Buda Pal; Manil Vaidhya; | Proceedings of International Conference on Innovation in … | 2026-01-19 |
| 107 | Can GPT-5.0 Interpret Thyroid Ultrasound Images? A Comparative TI-RADS Analysis with An Expert Radiologist Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study evaluates GPT-5.0’s ability to interpret thyroid US images according to TI-RADS criteria and contextualizes its performance relative to expert radiologist assessment, using FNA cytology as the reference standard. Methods: This retrospective study included 100 patients (mean age 49.8 ± 12.6 years; 72 women) with cytology-confirmed diagnoses: Bethesda II (benign) or Bethesda V–VI (malignant). |
Yunus Yasar; Sevde Nur Emir; Muhammet Rasit Er; Mustafa Demir; | Diagnostics | 2026-01-19 |
| 108 | A Novel Hybrid Model for Emotion Detection in Text Through Sequential and Transformer-based Approaches: LSTM Enhanced RoBERTa (LER) Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The results show that the hybrid approach efficiently detects intricate emotional cues, thus improving the state of emotion detection for real-world, context-sensitive applications. |
Bilal Khan; Muhammad Usman; Muhammad Binsawad; | Scientific Reports | 2026-01-19 |
| 109 | Capability-Aware Early-Stage Research Idea Evaluation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Our approach integrates author information, (inferred) capability presentation, and research ideas through a three-way transformer architecture with flexible fusion mechanisms. |
Renlong Jie; Chen Chu; Zhen Wang; | arxiv-cs.CL | 2026-01-18 |
| 110 | State of Charge Estimation of Battery for Electric Vehicle Based on VMD‐Basisformer Model Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To address challenges such as sensor noise, nonlinear dynamics, and complex temporal dependencies, this study proposes a novel VMD‐Basisformer model that integrates Variational Mode Decomposition (VMD) with an enhanced Basisformer neural network. |
YILING GAO et. al. | Quality and Reliability Engineering International | 2026-01-18 |
| 111 | BioPulse-QA: A Dynamic Biomedical Question-Answering Benchmark for Evaluating Factuality, Robustness, and Bias in Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: They also carry increasing risk of data leakage due to overlap with model pretraining corpora and often overlook critical dimensions such as robustness to linguistic variation and potential demographic biases. Materials and Methods: To address these gaps, we introduce BioPulse-QA, a benchmark that evaluates LLMs on answering questions from newly published biomedical documents including drug labels, trial protocols, and clinical guidelines. |
KRITI BHATTARAI et. al. | arxiv-cs.CL | 2026-01-18 |
| 112 | Predictive Prototyping: Evaluating Design Concepts with ChatGPT Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce a retrieval-augmented generation (RAG) method to emulate design feedback using OpenAI GPT-4o, grounded in prototyping data scraped from Instructables.com to increase access to relevant precedent. |
Hilsann Yong; Bradley A. Camburn; | arxiv-cs.HC | 2026-01-18 |
| 113 | Tolerance Principle and Small Language Model Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We trained BabyBERTa (Huebner et al. 2021), a transformer model optimized for small datasets, on artificial grammars. |
Adam E. Friedman; Stevan Harnad; Rushen Shi; | arxiv-cs.CL | 2026-01-17 |
| 114 | Predicting Biased Human Decision-Making with Large Language Models in Conversational Settings Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We examine whether large language models (LLMs) can predict biased decision-making in conversational settings, and whether their predictions capture not only human cognitive biases but also how those effects change under cognitive load. |
Stephen Pilli; Vivek Nallur; | arxiv-cs.HC | 2026-01-16 |
| 115 | Latency-Aware Benchmarking of Large Language Models for Natural-Language Robot Navigation in ROS 2 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This work introduces a latency-aware benchmarking framework that enables natural-language robot navigation by integrating multiple Large Language Models (LLMs) with the Robot Operating System 2 (ROS 2) Navigation 2 (Nav2) stack. |
Murat Das; Zawar Hussain; Muhammad Nawaz; | Sensors | 2026-01-16 |
| 116 | NLP-ROPCare: Predicting Retinopathy of Prematurity with Admission Notes Using Natural Language Processing Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Our study aimed to develop a new prediction model for ROP occurrence and severity, named NLP-ROPCare, using natural language processing (NLP). |
YULIN ZHANG et. al. | BMJ Open Ophthalmology | 2026-01-16 |
| 117 | Efficient Multilingual Name Type Classification Using Convolutional Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present a convolutional neural network approach for classifying proper names by language and entity type. |
Davor Lauc; | arxiv-cs.CL | 2026-01-16 |
| 118 | Human-AI Collaborative Inductive Thematic Analysis: AI Guided Analysis and Human Interpretive Authority Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Guided by a Human-Artificial Intelligence Collaborative Inductive Thematic Analysis (HACITA) framework, the study focuses on analytic process rather than substantive findings. |
MATTHEW NYAABA et. al. | arxiv-cs.AI | 2026-01-16 |
| 119 | The OB-GYN Take on GPT: Objective Assessment of Artificial Intelligence Models in Patient Education Related Papers Related Patents Related Grants Related Venues Related Experts View Save |
Lindsey Burleson; Ella Boardley; Alexandra LaShell; Anthony Shanks; | Cureus | 2026-01-15 |
| 120 | AI-Driven Objective Structured Clinical Examination Generation in Digital Health Education: Comparative Analysis of Three GPT-4o Configurations Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Objective This study aims to evaluate 3 GPT-4o configurations for generating OSCE stations in digital health: (1) standard GPT with a simple prompt and OSCE guidelines; (2) personalized GPT with a simple prompt, OSCE guidelines, and a reference book in digital health; and (3) simulated-agents GPT with a structured prompt simulating specialized OSCE agents and the digital health reference book. |
ZINEB ZOUAKIA et. al. | JMIR Medical Education | 2026-01-15 |
| 121 | LOOKAT: Lookup-Optimized Key-Attention for Memory-Efficient Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose LOOKAT, which applies product quantization and asymmetric distance computation, to transformer architecture by decomposing key vectors into subspaces, learning codebooks and computing attention tables via lookup tables. |
Aryan Karmore; | arxiv-cs.LG | 2026-01-15 |
| 122 | Transformer-Based Cognitive Radio: Adaptive Modulation Strategies Using Transformer Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This work investigates the application of Transformer models, specifically the GPT-2 architecture, to generate novel modulation schemes for wireless communications. |
Andrea Melis; Andrea Piroddi; Roberto Girau; | arxiv-cs.LG | 2026-01-15 |
| 123 | Empathy Applicability Modeling for General Health Queries Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce the Empathy Applicability Framework (EAF), a theory-driven approach that classifies patient queries in terms of the applicability of emotional reactions and interpretations, based on clinical, contextual, and linguistic cues. |
Shan Randhawa; Agha Ali Raza; Kentaro Toyama; Julie Hui; Mustafa Naseem; | arxiv-cs.CL | 2026-01-14 |
| 124 | Advanced Analysis of Leading Large Language Models for Diagnostic Accuracy in Retinal Imaging Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Methods We evaluated eight leading multimodal LLMs (GPT-4.5, Claude 3.7 Sonnet, Grok-2, Deepseek Cognition V2, Qwen2 72B, Gemini 2.0 Pro, Llama 3 405B and Mixtral 8×22B) on their ability to interpret 100 fundus images representing various ophthalmological conditions. |
MATTEO MARIO CARLÀ et. al. | British Journal of Ophthalmology | 2026-01-14 |
| 125 | Can LLMs Interpret Figurative Language As Humans Do?: Surface-level Vs Representational Similarity Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Large language models generate judgments that resemble those of humans. Yet the extent to which these models align with human judgments in interpreting figurative and socially … |
Samhita Bollepally; Aurora Sloman-Moll; Takashi Yamauchi; | arxiv-cs.CL | 2026-01-13 |
| 126 | Enhancing Sentiment Classification and Irony Detection in Large Language Models Through Advanced Prompt Engineering Techniques Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study investigates the use of prompt engineering to enhance large language models (LLMs), specifically GPT-4o-mini and gemini-1.5-flash, in sentiment analysis tasks. |
Marvin Schmitt; Anne Schwerk; Sebastian Lempert; | arxiv-cs.CL | 2026-01-13 |
| 127 | Advancing Cyberbullying Detection in Low-resource Languages: A Transformer- Stacking Framework for Bengali Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Many existing approaches overlook essential language-specific preprocessing, neglect the integration of advanced transformer-based models, and do not adequately address model validation, scalability, and adaptability. To address these limitations, this study introduces three Bengali-specific preprocessing strategies to enhance feature representation. |
Md. Nesarul Hoque; Rudra Pratap Deb Nath; Abu Nowshed Chy; Debasish Ghose; Md Hanif Seddiqui; | Frontiers in Artificial Intelligence | 2026-01-13 |
| 128 | Large Language Models for Psychiatric Diagnosis Based on Multicenter Real-World Clinical Records: Comparative Study Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Methods We retrospectively analyzed 9923 inpatient EHRs collected from 6 psychiatric centers across China, encompassing all ICD-10 (International Statistical Classification of Diseases, Tenth Revision) psychiatric categories. |
MAOQIAN SUN et. al. | JMIR Medical Informatics | 2026-01-13 |
| 129 | Knowledge-based Learning in Text-RAG and Image-RAG Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this research, we utilized the NIH Chest X-ray image to train the model and compared it in image-based RAG, text-based RAG, and baseline. |
Alexander Shim; Khalil Saieh; Samuel Clarke; | arxiv-cs.CV | 2026-01-13 |
| 130 | An Under-Explored Application for Explainable Multimodal Misogyny Detection in Code-mixed Hindi-English Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we present a multi-modal and explainable web application for detecting misogyny in text and memes in code-mixed Hindi and English. |
Sargam Yadav; Abhishek Kaushik; Kevin Mc Daid; | arxiv-cs.AI | 2026-01-13 |
| 131 | Contrastive Bi-Encoder Models for Multi-Label Skill Extraction: Enhancing ESCO Ontology Matching with BERT and Attention Mechanisms Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose a zero-shot skill extraction framework that eliminates the need for manually labeled job-ad training data. |
Yongming Sun; | arxiv-cs.CL | 2026-01-13 |
| 132 | Temporal Feature Mixed Inverted Transformer: An Inverted Transformer for Effective Real-time Electricity Price Forecasting Related Papers Related Patents Related Grants Related Venues Related Experts View Save |
Baichun Wang; Baoxian Huang; Qinglun Zhang; Yan Shi; Hong Men; | Engineering Applications of Artificial Intelligence | 2026-01-13 |
| 133 | Large Language Models and Creative Content Design: A Case Study of Email Marketing at Wine Access Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: A sequence of three randomized controlled trials (RCTs) is conducted to support a small online business’ decision of whether and how to implement AI in the creation of email … |
Jean-Pierre Dubé; Ariel Xu; | Quantitative Marketing and Economics | 2026-01-13 |
| 134 | A One-step Generation Model with A Single-Layer Transformer: Layer Number Re-distillation of FreeFlow Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We observe that the 28-layer Transformer architecture of FreeFlow can be characterized as an Euler discretization scheme for an ODE along the depth axis, where the layer index serves as the discrete time step. Therefore, we distill the number of layers of the FreeFlow model, following the same derivation logic as FreeFlow, and propose SLT (Single-Layer Transformer), which uses a single shared DiT block to approximate the depth-wise feature evolution of the 28-layer teacher. |
HAONAN WEI et. al. | arxiv-cs.CV | 2026-01-13 |
| 135 | Prompt-Based Clarity Evaluation and Topic Detection in Political Question Answering Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we study prompt-based clarity evaluation using the CLARITY dataset from the SemEval 2026 shared task. |
Lavanya Prahallad; Sai Utkarsh Choudarypally; Pragna Prahallad; Pranathi Prahallad; | arxiv-cs.CL | 2026-01-12 |
| 136 | GPT-4o and OpenAI O1 Performance on The 2024 Spanish Competitive Medical Specialty Access Examination: Cross-Sectional Quantitative Evaluation Study Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Objective The study aims to assess the performance of two LLMs—GPT-4o and OpenAI o1—on the Médico Interno Residente (MIR) 2024 examination, the Spanish national medical test that determines eligibility for competitive medical specialist training positions. |
PAU BENITO et. al. | JMIR Medical Education | 2026-01-12 |
| 137 | Large Language Model Performance in Clinical Cardiology Multiple Choice Questions; Has Reasoning Improved Performance? Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Purpose This study aims to compare the ability of Chat GPT-4o, GPT-4.5, GPT-o1, DeepSeek, and DeepSeek R1 to accurately respond to cardiology multiple choice questions (MCQs) from a commonly used UK cardiology textbook. |
R Crichton; B Liu; S Hothi; | European Heart Journal – Digital Health | 2026-01-12 |
| 138 | Transformer-Based Ensemble Model for Classification of Documents Based on English Vocabulary Words Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: While traditional classifiers and individual deep learning models achieve moderate success, they often struggle to capture both local lexical patterns and long-range contextual dependencies. To overcome these limitations, we propose a Transformer-based Ensemble Model that integrates BERT with Convolutional Neural Networks (CNNs) and Bidirectional Long Short-Term Memory (BiLSTMs) networks. |
Nisar Kangoo; Nisar Wani; | International Journal For Multidisciplinary Research | 2026-01-11 |
| 139 | Dynamical Systems Analysis Reveals Functional Regimes in Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Most interpretability approaches emphasise static representations or causal interventions, leaving temporal structure largely unexplored. Drawing on neuroscience, where temporal integration and metastability are core markers of neural organisation, we adapt these concepts to transformer models and discuss a composite dynamical metric, computed from activation time-series during autoregressive generation. |
Hassan Ugail; Newton Howard; | arxiv-cs.AI | 2026-01-11 |
| 140 | Extracting Structured Data from Unstructured Breast Imaging Reports with Transformer-based Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study compared the performance of BERT-based and generative language models in converting unstructured breast imaging reports into structured, tabular data suitable for clinical and research applications. |
Mikel Carrilero-Mardones; Jorge Pérez-Martín; Francisco Javier Díez; Iñigo Bermejo Delgado; | Frontiers in Digital Health | 2026-01-09 |
| 141 | A Transformer-Based Multi-Task Learning Framework for Sentiment, Emotion, and Sarcasm Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Abstract – A major challenge in natural language processing is determining the emotional intent of text because sentiment, emotion, and sarcasm all work together. |
Rohan Rajendra Chimbaikar; | International Journal of Scientific Research in Engineering … | 2026-01-09 |
| 142 | Enhancing E-Commerce Recommender System Inputs Using Transformer-Based Aspect-Based Sentiment Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Such aggregation often obscures feature-level preferences and limits the usefulness of sentiment outputs for personalization and decision support. To address this limitation, this study proposes a transformer-based ABSA pipeline that integrates KeyBERT for unsupervised aspect extraction with Bidirectional Encoder Representations from Transformers (BERT) for contextual sentiment classification at the aspect level. |
Dr. Nazima Khanam; Dr Karen Robinson; | International Journal of Latest Technology in Engineering … | 2026-01-09 |
| 143 | ChemGraph As An Agentic Framework for Computational Chemistry Workflows Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present ChemGraph, an agentic framework powered by artificial intelligence and state-of-the-art simulation tools to streamline and automate computational chemistry and materials science workflows. |
Thang D. Pham; Aditya Tanikanti; Murat Keçeli; | Communications Chemistry | 2026-01-08 |
| 144 | Vibe Coding An LLM-powered Theorem Prover Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present Isabellm, an LLM-powered theorem prover for Isabelle/HOL that performs fully automatic proof synthesis. |
Zhe Hou; | arxiv-cs.AI | 2026-01-08 |
| 145 | Comparative Performance Analysis of Large Language Models for Structured Data Processing: An Evaluation Framework Applied to Bibliometric Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce a reusable evaluation methodology incorporating five distinct prompt engineering techniques (Prefix, Cloze, Anticipatory, Heuristic, and Chain of Thought) applied to three categories of linguistic challenges: data extraction, aggregation, and contextual reasoning. |
MARYAM ABBASI et. al. | Applied Sciences | 2026-01-08 |
| 146 | AI-driven Risk Estimation: A GPT-based Approach to News Monitoring for Manufacturing Resilience Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Our research demonstrates the tool’s potential to enhance proactive risk management in supply chains, validated through testing on both real and augmented datasets. |
Adrian Jacob; Anas Ben Achour; Uwe Teicher; | The International Journal of Advanced Manufacturing … | 2026-01-08 |
| 147 | Evaluating Large Language Models’ Arabic Grammar Error Corrections and Explanations Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Arabic is one such language as it lacks linguistic materials such as annotated corpuses, language supporting models, and even Natural Language Processing (NLP) tools. The study reported in the article was designed to evaluate the performance of Large Language Models (LLMs) in GEC and in generating adequate and relevant explanations for these corrections. |
Kousar Mohi; Imtiaz Ahmad; Sa’ed Abed; | PeerJ Computer Science | 2026-01-08 |
| 148 | Effects of Personality Steering on Cooperative Behavior in Large Language Model Agents Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this study, we examine the effects of personality steering on cooperative behavior in LLM agents using repeated Prisoner’s Dilemma games. |
Mizuki Sakai; Mizuki Yokoyama; Wakaba Tateishi; Genki Ichinose; | arxiv-cs.AI | 2026-01-08 |
| 149 | Explainable Transformer-Based Modelling for Pathogen-Oriented Food Safety Inspection Grade Prediction Using New York State Open Data Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The objective of this study is to develop an explainable transformer-based framework for predicting food safety inspection grades using multimodal inspection data. |
Omer Faruk Sari; Mohamed Bader-El-Den; Volkan Ince; | Foods | 2026-01-08 |
| 150 | Geospatial Knowledge-Base Question Answering Using Multi-Agent Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Prior systems have relied on handcrafted rules and have omitted the splitting of datasets into training, validation, and test sets, thereby hindering fair evaluation. To address these gaps, we propose a prompt-based multi-agent LLM framework (based on GPT-4o) that translates natural-language questions into executable GeoSPARQL. |
Jonghyeon Yang; Jiyoung Kim; | ISPRS International Journal of Geo-Information | 2026-01-08 |
| 151 | Large Language Models Can Effectively Convince People to Believe Conspiracies Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Large language models (LLMs) have been shown to be persuasive across a variety of context. |
THOMAS H. COSTELLO et. al. | arxiv-cs.AI | 2026-01-08 |
| 152 | How Different Prompts Affect GPT-5s Chinese-to-English Translation Performance of Government Work Reports Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study examines the impact of different prompts – simple prompts, complex prompts, and few-shot prompts – on GPT-5s translation performance for the 2024 Chinese Government Work Report, finding that while complex prompts yielded better results in automatic evaluation metrics, human assessment showed no substantial differences in translation quality between simple and complex prompts. |
Jingjing Feng; | Advances in Humanities Research | 2026-01-08 |
| 153 | Cyber Threat Detection and Vulnerability Assessment System Using Generative AI and Large Language Model Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The proposed RoBERTa model achieved better results than the existing BERT model in terms of accuracy (0.99), recall (0.91), and precision (0.89) respectively. |
Keerthi Kumar. M; Swarun Kumar Joginpelly; Sunil Khemka; Lakshmi. S R; Navin Chhibber; | arxiv-cs.CR | 2026-01-08 |
| 154 | A Pilot Study on Multilingual Detection of Irregular Migration Discourse on X and Telegram Using Transformer-Based Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study presents an exploratory multilingual natural language processing (NLP) framework for detecting irregular migration discourse across five languages. |
Dimitrios Taranis; Gerasimos Razis; Ioannis Anagnostopoulos; | Electronics | 2026-01-08 |
| 155 | Beyond The Truth: Investigating Election Rumors on Truth Social During The 2024 Election Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Large language models (LLMs) offer unprecedented opportunities for analyzing social phenomena at scale. |
Etienne Casanova; R. Michael Alvarez; | arxiv-cs.AI | 2026-01-08 |
| 156 | Evaluating Few-shot Prompting for Spectrogram-based Lung Sound Classification Using A Multimodal Language Model Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Model repeatability analysis demonstrated high agreement (κ = 0.76–0.88; agreement: 89–96%), indicating excellent consistency. |
Nicholas Dietrich; David McShannon; Mark F. Rzepka; | PLOS Digital Health | 2026-01-07 |
| 157 | Large Language Models for Detecting Cyberattacks on Smart Grid Protective Relays Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents a large language model (LLM)-based framework for detecting cyberattacks on transformer current differential relays (TCDRs), which, if undetected, may trigger false tripping of critical transformers. |
AHMAD MOHAMMAD SABER et. al. | arxiv-cs.CR | 2026-01-07 |
| 158 | NorwAI’s Large Language Models: Technical Report Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To address this gap, the NorLLM team at NorwAI has developed a family of models specifically tailored to Norwegian and other Scandinavian languages, building on diverse Transformer-based architectures such as GPT, Mistral, Llama2, Mixtral and Magistral. These models are either pretrained from scratch or continually pretrained on 25B – 88.45B tokens, using a Norwegian-extended tokenizer and advanced post-training strategies to optimize performance, enhance robustness, and improve adaptability across various real-world tasks. |
Jon Atle Gulla; Peng Liu; Lemei Zhang; | arxiv-cs.CL | 2026-01-06 |
| 159 | The Performances of The Chinese and U.S. Large Language Models on The Topic of Chinese Culture Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To examine whether LLMs released by Chinese and U.S. developers exhibit cultural differences in Chinese-language settings, we evaluate their performance on questions about Chinese culture. |
Feiyan Liu; Chenxun Zhuo; Siyan Zhao; Bao Ge; Tianming Liu; | arxiv-cs.CL | 2026-01-06 |
| 160 | A Novel Unified Approach to Deepfake Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, a novel architecture for Deepfake detection in images and videos is presented. |
Lord Sen; Shyamapada Mukherjee; | arxiv-cs.CV | 2026-01-06 |
| 161 | Designing Conversational Intelligence: Effect of Large Language Models (GPT-Driven) Platforms for Precision Maternal and Newborn Health Engagement: A Systematic Review Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Large language models (LLM/GPTs), particularly GPT-driven conversational agents, have emerged as scalable, versatile digital health tools capable of delivering evidence-based information, mental health support, and risk stratification for complications such as preeclampsia, gestational diabetes, and preterm birth. Objective This systematic review aimed to synthesize global evidence on the design, implementation, and effectiveness of LLM/GPT-powered chatbots for precision maternal and newborn health engagement. |
Robab rasoli; Fahimeh Ebrahimisadrabadi; Zahra Khedri; Solmaz Sohrabei; | Oxford Open Digital Health | 2026-01-06 |
| 162 | Enhancing Aspect Category Sentiment Analysis Via Prompt-Based Prediction with Semantic Augmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, existing methodologies continue to face challenges of data scarcity and insufficient contextual understanding in short text sentiment analysis, with notable accuracy decline when processing implicit aspect expressions. This paper proposes a prompt-based RoBERTa-semantic model (PRSM) to address these complex issues. |
Ziwei Xiao; Junfeng Shen; | Physica Scripta | 2026-01-06 |
| 163 | Boosting Accuracy and Interpretability in Multilingual Hate Speech Detection Through Layer Freezing and Explainable AI Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this study, we examine the performance of three transformer-based models: BERT-base-multilingual-cased, RoBERTa-base, and XLM-RoBERTa-base with the first eight layers frozen, for multilingual sentiment analysis and hate speech detection. |
Meysam Shirdel Bilehsavar; Negin Mahmoudi; Mohammad Jalili Torkamani; Kiana Kiashemshaki; | arxiv-cs.CL | 2026-01-05 |
| 164 | Automating The Classification of Economic Activities in Official Statistics: A Comparative Study of Neural Networks and Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper explores the process of automation of the classification of open-ended questions regarding the economic activities of enterprises, in official statistics. |
Helda Curma; Valentina Sinaj; | WSEAS TRANSACTIONS ON COMPUTER RESEARCH | 2026-01-05 |
| 165 | Power-of-Two Quantization-Aware-Training (PoT-QAT) in Large Language Models (LLMs) Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we investigate compressing weights with a special quantization that limits numbers to only power-of-two (PoT). |
Mahmoud Elgenedy; | arxiv-cs.CL | 2026-01-05 |
| 166 | Is Sanskrit The Most Token-efficient Language? A Quantitative Study Using GPT, Gemini, and SentencePiece Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We use a dataset of 701 parallel verses of the Bhagavad Gita, which comprises three languages-Sanskrit, English, and Hindi along with transliteration of Sanskrit into English. |
Anshul Kumar; | arxiv-cs.CL | 2026-01-05 |
| 167 | Empirical Comparison of Encoder-Based Language Models and Feature-Based Supervised Machine Learning Approaches to Automated Scoring of Long Essays Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study trained several commonly used encoder-based language models for automated scoring of long essays. |
Kuo Wang; Haowei Hua; Pengfei Yan; Hong Jiao; Dan Song; | arxiv-cs.CL | 2026-01-05 |
| 168 | Adversarial Question Answering Robustness: A Multi-Level Error Analysis and Mitigation Study Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We perform comprehensive multi-level error analysis using five complementary categorization schemes, identifying negation confusion and entity substitution as the primary failure modes. |
Agniv Roy Choudhury; Vignesh Ponselvan Rajasingh; | arxiv-cs.CL | 2026-01-05 |
| 169 | Predicting Emergency Mortality Risk in Traumatic Brain Injury: Comparative Analysis of Machine Learning and Large Language Model GPT-5 Related Papers Related Patents Related Grants Related Venues Related Experts View Save |
KUAN-CHI TU et. al. | International Journal of Medical Informatics | 2026-01-05 |
| 170 | Perish or Flourish? A Holistic Evaluation of Large Language Models for Code Generation in Functional Programming Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, extensive evaluations of LLMs largely focus on imperative programming languages, and their capabilities in functional programming languages (FP) remain underexplored. To address this gap, we introduce FPEval, a holistic evaluation framework built on FPBench, a new benchmark of 721 programming tasks across three difficulty levels on three mainstream FP languages: Haskell, Ocaml and Scala. |
Nguyet-Anh H. Lang; Eric Lang; Thanh Le-Cong; Bach Le; Quyet-Thang Huynh; | arxiv-cs.PL | 2026-01-05 |
| 171 | When Do Tools and Planning Help LLMs Think? A Cost- and Latency-Aware Benchmark Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Modern large language models (LLMs) increasingly rely on inference-time planning and external tools to improve reasoning. We benchmark this behavior on two real-world settings: event-centric question answering over graph-structured knowledge (Event-QA) and persuasive response generation in Reddit ChangeMyView (CMV). |
Subha Ghoshal; Ali Al-Bustami; | arxiv-cs.CL | 2026-01-05 |
| 172 | Lightweight Transformer Architectures for Edge Devices in Real-Time Applications Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We establish real-time performance boundaries and provide a practical 6-step deployment pipeline achieving 8-12x size reduction with less than 2% accuracy degradation. |
Hema Hariharan Samson; | arxiv-cs.LG | 2026-01-04 |
| 173 | AI Chatbot As IFRS Advisory Tool: GPT‐4 Experimental Design Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Across all strategies, expert review remained necessary in areas involving item and measurement choices, contract integration, or business‐model interpretation. This study efforts to advance the dialogue on AI’s role in accounting and lays a foundation for future research exploring its broader implications in accounting decision‐making. |
Todor Tocev; Atanasko Atanasovski; | Intelligent Systems in Accounting, Finance and Management | 2026-01-03 |
| 174 | Detecting Hope in Social Media Discourse Using Machine and Deep Learning Classifiers Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, hope speech detection has received comparatively limited attention in social media discourse analysis when contrasted with tasks such as hate speech detection. This study addresses this gap by conducting both binary and multiclass classification of hope speech in two languages: (i) English and (ii) Spanish. |
Ahmad Imam Amjad; Hamza Imam Amjad; Grigori Sidorov; | International Journal of Combinatorial Optimization … | 2026-01-02 |
| 175 | Sentiment Analysis of TikTok User Comments on Student Proposal Hearing Videos Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study aims to analyze the sentiment and linguistic patterns of TikTok user comments on a student proposal hearing video to understand audience responses to academic content in digital media. |
Mugi Lestari; | International Journal of Linguistics, Communication, and … | 2026-01-02 |
| 176 | User Perceptions of An LLM-Based Chatbot for Cognitive Reappraisal of Stress: Feasibility Study Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study examined the feasibility of an LLM-based single-session intervention (SSI) for workplace stress reappraisal. |
Ananya Bhattacharjee; Jina Suh; Mohit Chandra; Javier Hernandez; | arxiv-cs.HC | 2026-01-02 |
| 177 | AraBART-based Arabic Lemmatization Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we introduce AraBART, the first Arabic model to feature an end-to-end pre-trained encoder-decoder, leveraging the BART architecture. |
Soumia Afartass; Fadoua Ataa Allah; Khalid Minaoui; | WSEAS TRANSACTIONS ON INFORMATION SCIENCE AND APPLICATIONS | 2026-01-02 |
| 178 | Adapting Feature Attenuation to NLP Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Concretely, we adapt the COSTARR framework–originally designed for classification in computer vision–to two modest language models (BERT (base) and GPT-2) trained to label 176 arXiv subject areas. |
Tianshuo Yang; Ryan Rabinowitz; Terrance E. Boult; Jugal Kalita; | arxiv-cs.LG | 2026-01-02 |
| 179 | Improving Router Security Using BERT Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we demonstrate that using a high-fidelity eBPF-based system call sensor, together with contrastive augmented learning (which introduces controlled mutations of negative samples), improves detection performance at a low false positive rate. |
John Carter; Spiros Mancoridis; Pavlos Protopapas; Brian Mitchell; Benji Lilley; | arxiv-cs.CR | 2026-01-02 |
| 180 | A Comparative Study of Deep Learning and Transformer Models for Twitter Sentiment Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we investigate sentiment classification on Twitter using the Sentiment140 dataset and compare traditional deep learning approaches, including CNN, BiLSTM, and GRU, with a lightweight transfer learning model, DistilBERT. |
FATIMA HAFEEZ et. al. | International Journal of Combinatorial Optimization … | 2026-01-02 |
| 181 | GPT-5 and Open-weight Large Language Models: Advances in Reasoning, Transparency, and Control Related Papers Related Patents Related Grants Related Venues Related Experts View Save |
Maikel Leon; | Inf. Syst. | 2026-01-01 |
| 182 | Shield Broken: Black-Box Adversarial Attacks on LLM-Based Vulnerability Detectors Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Vulnerability detection is critical for ensuring software security. Although deep learning (DL) methods, particularly those employing large language models (LLMs), have shown … |
Yuan Jiang; Shan Huang; Christoph Treude; Xiaohong Su; Tiantian Wang; | IEEE Transactions on Software Engineering | 2026-01-01 |
| 183 | Comparative Efficiency Analysis of Lightweight Transformer Models: A Multi-Domain Empirical Benchmark for Enterprise NLP Deployment Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study conducts a comparative analysis of three prominent lightweight Transformer models – DistilBERT, MiniLM, and ALBERT – across three distinct domains: customer sentiment classification, news topic classification, and toxicity and hate speech detection. |
Muhammad Shahmeer Khan; | arxiv-cs.CL | 2026-01-01 |
| 184 | Modeling Language As A Sequence of Thoughts Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: On the other hand, cognitive science shows that human comprehension involves converting the input linguistic stream into compact, event-like representations that persist in memory while verbatim form is short-lived. Motivated by this view, we introduce Thought Gestalt (TG) model, a recurrent Transformer that models language at two levels of abstraction – tokens and sentence-level thought states. |
Nasim Borazjanizadeh; James McClelland; | arxiv-cs.CL | 2025-12-31 |
| 185 | Exploring GPT-Based Multi-agent Collaboration for Automated Market Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study explores a no-code experimental framework using a multi-agent system built upon GPT to perform automated market analysis. |
Guocheng Hou; | Applied and Computational Engineering | 2025-12-31 |
| 186 | The Efficacy of Artificial Intelligence in Future Anatomy Education: A Duel of Ideas with ChatGPT-4o Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study aims to assess the effectiveness, reliability, and proficiency of GPT-4o in anatomy education and to explore how artificial intelligence (AI) can make learning more accessible and memorable for medical students, while also addressing some of the challenges associated with its use in education. |
İsmet Demirtaş; | Uluslararası Yönetim Bilişim Sistemleri ve Bilgisayar … | 2025-12-31 |
| 187 | IELTS Writing Revision Platform with Automated Essay Scoring and Adaptive Feedback Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents the design, development, and evaluation of a proposed revision platform assisting candidates for the International English Language Testing System (IELTS) writing exam. |
Titas Ramancauskas; Kotryna Ramancauske; | arxiv-cs.CL | 2025-12-30 |
| 188 | Enhancing English Language Learning Through Moral Dilemmas: A Comparative Study of GPT and Human-written Stories Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study investigates the effects of generative pre-trained transformer (GPT) generated vs. human-written moral dilemma stories on English as a foreign language (EFL) learners’ speaking skills, storytelling ability, and behavioral regulation, framed within the theoretical context of embodied cognition. |
Jiaqi Wang; Chengliang Wang; Tong Xiao; Xinyu Zhang; | Language Teaching Research | 2025-12-30 |
| 189 | Weakly‐Aligned Region‐Language Transformer for Real‐Time Artistic Content Detection in SAGIN Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: These challenges include limited on‐board computational capacity, fluctuating bandwidth, and the requirement for fine‐grained visual‐semantic reasoning under weak supervision. To overcome these limitations, we propose the Weakly‐Aligned Region‐Language Transformer (WARL‐Transformer), a novel framework designed for robust AI‐generated content detection under realistic SAGIN constraints. |
Jiayue Yu; Sudip Kumar Sahana; | Transactions on Emerging Telecommunications Technologies | 2025-12-30 |
| 190 | INTEGRASI ALGORITMA NLP UNTUK PENINGKATAN KECERDASAN CHATBOT: KAJIAN LITERATUR DAN ANALISIS PERKEMBANGAN TERKINI Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study aims to map NLP algorithm trends, application domains, and future research directions. |
Razan Muhammad Rizqi; Devano Agastya Harshavardana; Sulthan Valeri Osmond R; | Jurnal Riset Teknik Komputer | 2025-12-30 |
| 191 | Detection and Classification of Ideological Texts in The Kazakh Language Using Machine Learning and Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper examines deep learning methods and transformers models for the automatic classification of ideologically charged texts in the Kazakh language. |
Milana Bolatbek; Shynar Mussiraliyeva; Kymbat Baisylbayeva; | Research in Language | 2025-12-30 |
| 192 | Guiding A Diffusion Transformer with The Internal Dynamics of Itself Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The diffusion model presents a powerful ability to capture the entire (conditional) data distribution. |
Xingyu Zhou; Qifan Li; Xiaobin Hu; Hai Chen; Shuhang Gu; | arxiv-cs.CV | 2025-12-30 |
| 193 | FedLiTeCAN : A Federated Lightweight Transformer for Fast and Robust CAN Bus Intrusion Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This work implements a lightweight Transformer model for IDS in the domain of Connected and Autonomous Vehicles |
Devika S; Pratik Narang; Tejasvi Alladi; | arxiv-cs.CR | 2025-12-30 |
| 194 | WISE: Web Information Satire and Fakeness Evaluation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study develops WISE (Web Information Satire and Fakeness Evaluation) framework which benchmarks eight lightweight transformer models alongside two baseline models on a balanced dataset of 20,000 samples from Fakeddit, annotated as either fake news or satire. |
Gaurab Chhetri; Subasish Das; Tausif Islam Chowdhury; | arxiv-cs.CL | 2025-12-30 |
| 195 | MedGemma Vs GPT-4: Open-Source and Proprietary Zero-shot Medical Disease Classification from Images Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Multimodal Large Language Models (LLMs) introduce an emerging paradigm for medical imaging by interpreting scans through the lens of extensive clinical knowledge, offering a transformative approach to disease classification. |
Md. Sazzadul Islam Prottasha; Nabil Walid Rafi; | arxiv-cs.CV | 2025-12-29 |
| 196 | StressRoBERTa: Cross-Condition Transfer Learning from Depression, Anxiety, and PTSD to Stress Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper introduces StressRoBERTa, a cross-condition transfer learning approach for automatic detection of self-reported chronic stress in English tweets. |
Amal Alqahtani; Efsun Kayi; Mona Diab; | arxiv-cs.CL | 2025-12-29 |
| 197 | Benchmarking Cross-Lingual Semantic Alignment in Multilingual Embeddings Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce Semantic Affinity (SA), a bounded (between 0 and 1) metric measuring inter-lingual to intra-lingual spread ratio using cosine distance, combined with PHATE visualization in our Semanscope framework. |
Wen G. Gong; | arxiv-cs.CL | 2025-12-29 |
| 198 | Deep Learning for Pedestrians: Backpropagation in Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To this end, we apply our lightweight index-free methodology to new types of layers such as embedding, multi-headed self-attention and layer normalization. |
Laurent Boué; | arxiv-cs.LG | 2025-12-29 |
| 199 | Performance Comparison of Large Language Models on Pediatric Dentistry Questions in The Turkish Dentistry Specialization Examination Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Future research should evaluate and enhance LLMs’ multimodal and visual‑data processing capabilities to improve clinical applicability. |
Hatice Kübra Başkan; Beyhan Başkan; | BMC Medical Education | 2025-12-29 |
| 200 | Splitwise: Collaborative Edge-Cloud Inference for LLMs Via Lyapunov-Assisted DRL Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose Splitwise, a novel Lyapunov-assisted deep reinforcement learning (DRL) framework for fine-grained, adaptive partitioning of LLMs across edge and cloud environments. |
ABOLFAZL YOUNESI et. al. | arxiv-cs.LG | 2025-12-29 |
| 201 | Explaining News Bias Detection: A Comparative SHAP Analysis of Transformer Model Decision Mechanisms Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we present a comparative interpretability study of two transformer-based bias detection models: a bias detector fine-tuned on the BABE dataset and a domain-adapted pre-trained RoBERTa model fine-tuned on the BABE dataset, using SHAP-based explanations. |
Himel Ghosh; | arxiv-cs.CL | 2025-12-29 |
| 202 | How Emotional Content in Tweets Drive Funding Success? – A Study on Indian Startups Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Purpose This study aims to explore how emotional expressions in startups’ social media posts influence funding outcomes, with a focus on multiple dimensions of emotions using the Circumplex model. |
Nidhi Singhal; Neelmani Gupta; Deepak Kapur; | Journal of Entrepreneurship in Emerging Economies | 2025-12-29 |
| 203 | Evaluating The Appropriateness and Safety of Generative AI in Delivering Lifestyle Guidance for Atrial Fibrillation Patients Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study assessed the clinical utility of three Large Language Models (LLMs) for delivering accurate and personalized lifestyle guidance: (1) GPT-4o, (2) a retrieval-augmented model using a curated Q&A database (DB GPT), and (3) a modular RAG model retrieving evidence from PubMed (PubMed GPT). |
Masahiro Makino; Wan Jou She; Panote Siriaraya; Satoaki Matoba; Keitaro Senoo; | Scientific Reports | 2025-12-29 |
| 204 | A Comparative Benchmark Study of Large Language Models on Turkish NLP Tasks: A Comparison of ChatGPT and DeepSeek Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study presents a comprehensive performance evaluation of two leading LLMs, ChatGPT (GPT-4o) and DeepSeek-v3, on Turkish NLP tasks, addressing challenges in low-resource and morphologically complex languages. |
Emre Ünsal; Ahmet Turan Karakuş; | International Journal of Innovative Engineering Applications | 2025-12-29 |
| 205 | A Review on Fake News Detection and Personalized Recommendation on Social Media Using BERT Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents a comprehensive review of transformer-based fake news detection approaches, particularly those utilizing Bidirectional Encoder Representations from Transformers (BERT), along with Feder- ated Learning techniques for secure and decentralized personalization. |
Adithya A A; | International Journal for Research in Applied Science and … | 2025-12-28 |
| 206 | HELM-BERT: A Transformer for Medium-sized Peptide Property Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Here, we propose HELM-BERT, the first encoder-based peptide language model trained on HELM notation. |
Seungeon Lee; Takuto Koyama; Itsuki Maeda; Shigeyuki Matsumoto; Yasushi Okuno; | arxiv-cs.LG | 2025-12-28 |
| 207 | CNSight: Evaluation of Clinical Note Segmentation Tools Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we evaluate rule-based baselines, domain-specific transformer models, and large language models for clinical note segmentation using a curated dataset of 1,000 notes from MIMIC-IV. |
RISHA SURANA et. al. | arxiv-cs.CL | 2025-12-28 |
| 208 | Advanced Cross-Validation Framework for Mental Health AI: BERT and Neural Networks Achieve High Accuracy on Mental Chat16K Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study presents a comprehensive analysis of the MentalChat16K dataset, which contains 16,084 mental health conversation pairs (6,338 real clinical interviews and 9,746 synthetic dialogues), using modern deep learning architectures. |
Irfan Ali; | Indian Journal of Artificial Intelligence and Neural … | 2025-12-27 |
| 209 | Fake News Classification in Urdu: A Domain Adaptation Approach for A Low-Resource Language Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We evaluate two widely used multilingual models, XLM-RoBERTa and mBERT, and apply domain-adaptive pretraining using a publicly available Urdu news corpus. |
Muhammad Zain Ali; Bernhard Pfahringer; Tony Smith; | arxiv-cs.CL | 2025-12-27 |
| 210 | GHaLIB: A Multilingual Framework for Hope Speech Detection in Low-Resource Languages Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents a multilingual framework for hope speech detection with a focus on Urdu. |
Ahmed Abdullah; Sana Fatima; Haroon Mahmood; | arxiv-cs.CL | 2025-12-27 |
| 211 | FedEnsemble: Federated Learning Model for Efficient Sentiment Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, deploying state-of-the-art transformer-based models in real-world applications poses two key challenges: preserving user data privacy and mitigating the computational overhead associated with large-scale models. This study introduces FedEnsemble, a novel federated learning framework that addresses these challenges through three core innovations: (i) a heterogeneous ensemble of BERT, RoBERTa, and DistilBERT to enhance classification robustness; (ii) an entropy-based attention stacking mechanism that adaptively fuses model outputs according to predictive confidence; and (iii) Quantization-Aware Training (QAT) to compress models while maintaining high accuracy and communication efficiency. |
Hesham Ayman; Shaimaa Haridy; Yasmine M. Afify; Walaa Gad; | Computing | 2025-12-26 |
| 212 | Evaluating The Performance of AI Large Language Models in Detecting Pediatric Medication Errors Across Languages: A Comparative Study Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study highlights the importance of human oversight and domain-based training for AI tools in pediatric pharmacotherapy. |
RANA K. ABU-FARHA et. al. | Journal of Clinical Medicine | 2025-12-25 |
| 213 | Detecting AI-Generated Paraphrases in Bengali: A Comparative Study of Zero-Shot and Fine-Tuned Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study investigates five transformer-based models: XLMRoBERTa-Large, mDeBERTaV3-Base, BanglaBERT-Base, IndicBERT-Base and MultilingualBERT-Base. |
Md. Rakibul Islam; Most. Sharmin Sultana Samu; Md. Zahid Hossain; Farhad Uz Zaman; Md. Kamrozzaman Bhuiyan; | arxiv-cs.CL | 2025-12-25 |
| 214 | From LSTM to GPT-2: Recurrent and Transformer-Based Deep Learning Architectures for Multivariate High-Liquidity Cryptocurrency Price Forecasting Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study introduces a unified and methodologically symmetric comparative framework for multivariate cryptocurrency forecasting, addressing long-standing inconsistencies in prior research where model families, feature sets, and preprocessing pipelines differ across studies. |
Erçin Dinçer; Zeynep Hilal Kilimci; | Symmetry | 2025-12-24 |
| 215 | Computer Assisted Verbal Autopsy: Comparing Large Language Models to Physicians for Assigning Causes to 6939 Deaths in Sierra Leone from 2019–2022 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Methods We analyzed 6,939 VA records from a random sample of deaths in Sierra Leone (2019–2022) to compare five models: three LLMs (GPT-3.5, GPT-4, GPT-5) and two based on symptom algorithms (InterVA-5, InSilicoVA), against physician-assigned CODs. |
RICHARD WEN et. al. | BMC Medicine | 2025-12-24 |
| 216 | Medical QA Dialogue Datasets in RAG Systems Performance Evaluation and ChatGPT Optimization Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Using ChatGPT-3.5 as a baseline and extending to GPT-4o and GPT-5, we compare multiple retrieval pipelines, including dense retrieval, Cross-Encoder reranking, Reciprocal Rank Fusion (RRF), and Cascade RRF→Rerank. |
Muretijiang Muhetaer; Ailimulati Yusupu; Wang Yifan; Munire Mutalipu; Fan Hao; | Scientific Reports | 2025-12-24 |
| 217 | Comparative Evaluation of GPT-4o, GPT-OSS-120B and Llama-3.1-8B-Instruct Language Models in A Reproducible CV-to-JSON Extraction Pipeline Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study introduces a deterministic, GDPR-aligned pipeline that converts recruitment documents into structured, anonymized Markdown and subsequently into validated JSON ready for downstream AI processing. |
MARCIN NAWALNY et. al. | Applied Sciences | 2025-12-24 |
| 218 | SMART SLM: Structured Memory and Reasoning Transformer, A Small Language Model for Accurate Document Assistance Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The user of Engineering Manuals (EM) finds it difficult to read EM s because they are long, have a dense format which includes written documents, step by step procedures, and standard parameter lists for engineering equipment. |
Divij Dudeja; Mayukha Pal; | arxiv-cs.CL | 2025-12-24 |
| 219 | Automatic Replication of LLM Mistakes in Medical Conversations Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Yet, replicating specific mistakes in other LLM models is not straightforward and often requires manual effort. We introduce MedMistake, an automatic pipeline that extracts mistakes LLMs make in patient-doctor conversations and converts them into a benchmark of single-shot QA pairs. |
Oleksii Proniakin; Diego Fajardo; Ruslan Nazarenko; Razvan Marinescu; | arxiv-cs.CL | 2025-12-24 |
| 220 | SentXFormer: A Transformer-enhanced Hybrid Deep Learning Framework for Cross-domain Sentiment Analysis of Customer Reviews IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents a deep learning model named SentXFormer, which is a transformer-based hybrid framework that enhances the sentiment classification in heterogeneous domains. |
Ajeet Kumar; Kumar Abhishek; Ahamed Shafeeq B M; | Scientific Reports | 2025-12-24 |
| 221 | Evaluation of Cutting-Edge Object Detection Architectures on Multi-Object and Single-Object Datasets Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study focuses on the performance evaluation of mainstream object detection model, namely, YOLO12, Mask-RCNN, RT-DETR, and RF-DETR on the Open Images (Multi-Object) and LaSOT (Single-Object) datasets. |
Cevahir Parlak; | Black Sea Journal of Engineering and Science | 2025-12-24 |
| 222 | Multi-LLM Thematic Analysis with Dual Reliability Metrics: Combining Cohen’s Kappa and Semantic Similarity for Qualitative Research Validation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present a multi-perspective validation framework for LLM-based thematic analysis that combines ensemble validation with dual reliability metrics: Cohen’s Kappa ($κ$) for inter-rater agreement and cosine similarity for semantic consistency. |
Nilesh Jain; Seyi Adeyinka; Leor Roseman; Aza Allsop; | arxiv-cs.CL | 2025-12-23 |
| 223 | Nemotron 3 Nano: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present Nemotron 3 Nano 30B-A3B, a Mixture-of-Experts hybrid Mamba-Transformer language model. |
AARON BLAKEMAN et. al. | arxiv-cs.CL | 2025-12-23 |
| 224 | A Dataset and Preliminary Study of Using GPT-5 for Code-change Impact Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, the extent to which this potential can be utilized for understanding code changes and their impact is underexplored. To address this gap, we study the capabilities of GPT-5 and GPT-5-mini to predict the code entities impacted by given source code changes. |
Katharina Stengg; Christian Macho; Martin Pinzger; | arxiv-cs.SE | 2025-12-22 |
| 225 | Performance of Large Language Models in Lung Cancer Clinical Decision-Making: A Comparative Analysis Based on DeepSeek, Grok, and GPT Related Papers Related Patents Related Grants Related Venues Related Experts View Save |
Yuyang Zhang; Dandan Yang; Yifan Shi; Ying Liu; | Cureus | 2025-12-22 |
| 226 | Impact of Parameter-To-Data Ratio on LLM Fine-Tuning in Russian Text Classification Tasks Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper addresses the optimization of fine-tuning large language models (LLMs) for Russian-language text classification under constrained computational resources. |
Fedor Shamigov; | Virtual Communication and Social Networks | 2025-12-22 |
| 227 | Scrum Sprint Planning: LLM-based and Algorithmic Solutions Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Planning for an upcoming project iteration (sprint) is one of the key activities in Scrum planning. In this paper, we present our work in progress on exploring the applicability of Large Language Models (LLMs) for solving this problem. |
YUWON YOON et. al. | arxiv-cs.SE | 2025-12-21 |
| 228 | Transformer Reconstructed with Dynamic Value Attention Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: I propose a method to decide a value for each query dynamically, which could cut down all the redundant heads, keeping only one. |
Xiaowei Wang; | arxiv-cs.LG | 2025-12-21 |
| 229 | InstructNet: A Novel Approach for Multi-Label Instruction Classification Through Advanced Deep Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study uses the How To articles to determine the multi-label instruction category. |
Tanjim Taharat Aurpa; Md Shoaib Ahmed; Md Mahbubur Rahman; Md. Golam Moazzam; | arxiv-cs.CL | 2025-12-20 |
| 230 | BERT-MED Chatbot for Healthcare Assistance Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper introduces BERT-MED, an AI-driven healthcare assistance system that follows templates. |
Champa M S; Prajwal D R; Puneeth H K; Pola Manoj Kumar; Shreyank T N; | International Journal of Scientific Research in Engineering … | 2025-12-20 |
| 231 | A Review on Handwritten Malayalam to English Digitization and Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The review covers a range of methodologies, including classical Optical Character Recognition (OCR) techniques, statistical machine translation (SMT), neural machine translation (NMT), and new Vision Language Models (VLMs). |
Mohammed Farhan; | International Journal for Research in Applied Science and … | 2025-12-20 |
| 232 | ScoutGPT: Capturing Player Impact from Team Action Sequences Using GPT-Based Framework Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Existing evaluation practices often rely on static summary statistics or post-hoc value models, which fail to capture how a player’s contribution adapts to a new tactical environment or different teammates. To address this gap, we introduce EventGPT, a player-conditioned, value-aware next-event prediction model built on a GPT-style autoregressive transformer. |
MIRU HONG et. al. | arxiv-cs.AI | 2025-12-19 |
| 233 | ESummarizer AI Service- Document Summarization Model Using BART Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This research presents eSummarizer AI Service, a custom Transformer-based machine learning model designed specifically for summarizing Indian government documents such as policy papers, circulars, legislative texts, and departmental reports. |
Rongdeep Pathak; Mriganka Mohan Bora; Nelson R Varte; | International Journal of Latest Technology in Engineering … | 2025-12-19 |
| 234 | Advances and Challenges in Semantic Textual Similarity: A Comprehensive Survey Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This survey reviews progress across six key areas: transformer-based models, contrastive learning, domain-focused solutions, multi-modal methods, graph-based approaches, and knowledge-enhanced techniques. |
Lokendra Kumar; Neelesh S. Upadhye; Kannan Piedy; | arxiv-cs.CL | 2025-12-19 |
| 235 | Confidence-Credibility Aware Weighted Ensembles of Small LLMs Outperform Large LLMs in Emotion Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper introduces a confidence-weighted, credibility-aware ensemble framework for text-based emotion detection, inspired by Condorcet’s Jury Theorem (CJT). |
Menna Elgabry; Ali Hamdi; | arxiv-cs.CL | 2025-12-19 |
| 236 | OpenAI GPT-5 System Card Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We’ve made significant advances in reducing hallucinations, improving instruction following, and minimizing sycophancy, and have leveled up GPT-5’s performance in three of ChatGPT’s most common uses: writing, coding, and health. |
AADITYA SINGH et. al. | arxiv-cs.CL | 2025-12-19 |
| 237 | Bangla MedER: Multi-BERT Ensemble Approach for The Recognition of Bangla Medical Entity Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: A major challenge in MedER for low-resource languages is the lack of annotated datasets. To address this issue, we developed a high-quality dataset tailored for the Bangla MedER task. |
TANJIM TAHARAT AURPA et. al. | arxiv-cs.CL | 2025-12-19 |
| 238 | A Hybrid Deep Learning Model Based on Local and Global Features for Amazon Product Reviews: An Optimal ALBERT-Cascade CNN Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To address these challenges, in this study, the researchers first performed a series of ablation experiments on 14 models derived from various variations in Deep Learning (DL) methods, including A Lite BERT (ALBERT) together with Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM), Bidirectional LSTM (BiLSTM), Max Pooling layer, and attention mechanism. Subsequently, they proposed an ALBERT-cascaded CNN hybrid model as an effective method to overcome the related challenges by evaluating the performance results obtained from these models. |
Israa Mustafa Abbas; İsmail Atacak; Sinan Toklu; Necaattin Barışçı; İbrahim Alper Doğru; | Applied Sciences | 2025-12-19 |
| 239 | A Review of Sentiment Analysis Research Based on BERT and Its Improved Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: A series of improved models such as RoBERTa-wwm-ext, ERNIE, ALBERT-zh, and MacBERT continued to refresh performance records in Chinese sentiment analysis tasks. This paper systematically reviews the research progress of sentiment analysis based on BERT and its improved models in recent years. |
Jingxuan Chen; | Science and Technology of Engineering, Chemistry and … | 2025-12-19 |
| 240 | Predictive Modeling of Maritime Radar Data Using Transformer Architecture Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This survey systematically reviews predictive modeling approaches relevant to maritime radar, with emphasis on transformer architectures for spatiotemporal sequence forecasting, where existing representative methods are analyzed according to data type, architecture, and prediction horizon. |
Bjorna Qesaraku; Jan Steckel; | arxiv-cs.CV | 2025-12-18 |
| 241 | Emergent World Beliefs: Exploring Transformers in Stochastic Games Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Prior work has shown that LLMs can develop emergent world models in games of perfect information, where internal representations correspond to latent states of the environment. In this paper, we extend this line of investigation to domains of incomplete information, focusing on poker as a canonical partially observable Markov decision process (POMDP). |
Adam Kamel; Tanish Rastogi; Michael Ma; Kailash Ranganathan; Kevin Zhu; | arxiv-cs.CL | 2025-12-18 |
| 242 | Benchmarking and Adapting On-Device Large Language Models for Clinical Decision Support Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Large language models (LLMs) have rapidly advanced in clinical decision-making, yet the deployment of proprietary systems is hindered by privacy concerns and reliance on cloud-based infrastructure. |
ALIF MUNIM et. al. | arxiv-cs.CL | 2025-12-18 |
| 243 | Exploration of Augmentation Strategies in Multi-modal Retrieval-Augmented Generation for The Biomedical Domain: A Case Study Evaluating Question Answering in Glycobiology Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We evaluated mid-size open-source and frontier proprietary models (e.g., Gemma-3-27B-IT, GPT-4o family). |
PRIMOŽ KOCBEK et. al. | arxiv-cs.CL | 2025-12-18 |
| 244 | UM_FHS at The CLEF 2025 SimpleText Track: Comparing No-Context and Fine-Tune Approaches for GPT-4.1 Models in Sentence and Document-Level Text Simplification Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This work describes our submission to the CLEF 2025 SimpleText track Task 1, addressing both sentenceand document-level simplification of scientific texts. |
Primoz Kocbek; Gregor Stiglic; | arxiv-cs.CL | 2025-12-18 |
| 245 | Plain Language Adaptations of Biomedical Text Using LLMs: Comparision of Evaluation Metrics Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Using a public dataset, which included plain language adaptations of biomedical abstracts, we developed and evaluated several approaches, specifically a baseline approach using a prompt template, a two AI agent approach, and a fine-tuning approach. |
Primoz Kocbek; Leon Kopitar; Gregor Stiglic; | arxiv-cs.CL | 2025-12-18 |
| 246 | Radiology Report Generation with Layer-Wise Anatomical Attention Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce a compact image-to-text architecture that generates the Findings section of chest X-ray reports from a single frontal image. |
EMMANUEL D. MUÑIZ-DE-LEÓN et. al. | arxiv-cs.CV | 2025-12-18 |
| 247 | LLMCache: Layer-Wise Caching Strategies for Accelerated Reuse in Transformer Inference Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we present LLMCache, a novel layer-wise caching framework that accelerates transformer inference by reusing intermediate activations based on semantic similarity of input sequences. |
Harsh Vardhan Bansal; | arxiv-cs.CL | 2025-12-18 |
| 248 | NRGPT: An Energy-based Alternative for GPT Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose a minimal modification of the GPT setting to unify it with the EBM framework. |
NIMA DEHMAMY et. al. | arxiv-cs.LG | 2025-12-18 |
| 249 | PhishGuard: AI-Driven Graph-Based Analysis for Smarter Email Security Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This project proposes a dual-model solution: a RoBERTa-based transformer is used to classify the email body content, while a Neo4j-powered graph model analyses sender-receiver domain relationships using graph metrics such as PageRank, ArticleRank, and Degree Centrality. |
Harchana Ramesh; Noris Ismail; ; Nor Azlina Abd Rahman; ; Aitizaz Ali; | STAP Journal of Security Risk Management | 2025-12-18 |
| 250 | When Jack of All Trades Is A Master of None: Comparing The Performance of GPT-4 Omni Against Specialised Neural Networks in Identifying Malignant Dermatological Lesions from Smartphone Images and Structured Clinical Data Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: General-purpose multimodal large language models (LLMs), such as GPT-4o, have not been rigorously evaluated for this task. This study assessed GPT-4o’s ability to triage skin lesions and compared its performance to specialised neural networks. |
JIAWEN DENG et. al. | Dermatology | 2025-12-18 |
| 251 | Enhancing Energy Distribution Efficiency with Dynamic Transformer Rotation in 11kV Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study presents the optimisation of transformer-to-feeder load allocation within an 11kV distribution network to improve energy distribution efficiency, minimise transformer overload, and enhance system balance. |
Jewel Idehen; Dennis Okonkwo; Michael Atu; Ikenna Onyegbadue; | Lafia Journal of Scientific and Industrial Research | 2025-12-17 |
| 252 | Cutting-edge Technologies for Analyzing Student Feedback to Inform Institutional Decision-making in Higher Education Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study presents a multitask learning framework to analyze student evaluations of teaching (SET) by extracting and classifying opinions on specific aspects of teaching performance. |
Sabur Butt; Sandra Dennis Núñez Daruich; Joanna Alvarado-Uribe; Hector G. Ceballos; | Foresight and STI Governance | 2025-12-17 |
| 253 | Performance of GPT‐5 in The Interpretation of IBD Histopathology Reports Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Methods We analyzed 100 real‐life histological reports from ileo‐colonoscopies, equally representing CD, UC, IBD‐U, and NIBDC, collected across five Italian healthcare centers, including both IBD‐specialized and non‐specialized hospitals. |
MARCELLO MAIDA et. al. | United European Gastroenterology Journal | 2025-12-17 |
| 254 | Reasoning‐optimised Large Language Models Reach Near‐expert Accuracy on Board‐style Orthopaedic Exams: A Multi‐model Comparison on 702 Multiple‐choice Questions Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Abstract Purpose The purpose of this study was to compare the accuracy, calibration, reproducibility and operating cost of seven large language models (LLMs)—including four newer models capable of using advanced reasoning techniques to analyse complex medical information and generate accurate responses—on text‐only orthopaedic multiple‐choice questions (MCQs) and to quantify gains over GPT‐4. |
PEDRO DINIZ et. al. | Knee Surgery, Sports Traumatology, Arthroscopy | 2025-12-17 |
| 255 | When A Nation Speaks: Machine Learning and NLP in People’s Sentiment Analysis During Bangladesh’s 2024 Mass Uprising Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Through Latent Dirichlet Allocation (LDA), we identified prevalent themes like political corruption and public protests, and analyzed how events such as internet blackouts shaped sentiment patterns. |
Md. Samiul Alim; Mahir Shahriar Tamim; Maisha Rahman; Tanvir Ahmed Khan; Md Mushfique Anwar; | arxiv-cs.CL | 2025-12-17 |
| 256 | Adaptive Cache Pollution Control for Large Language Model Inference Workloads Using Temporal CNN-Based Prediction and Priority-Aware Replacement Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Large Language Models (LLMs), such as GPT and LLaMA, introduce unique memory access characteristics during inference due to frequent token sequence lookups and embedding vector retrievals. |
Songze Liu; Hongkun Du; Shaowen Wang; | arxiv-cs.AR | 2025-12-16 |
| 257 | Multiple Large Language Models’ Performance on The Chinese Medical Licensing Examination: Quantitative Comparative Study Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We evaluated the accuracy, comprehensiveness, and logical coherence of the responses, with quantitative comparison centered on scores and accuracy rates against the official answer keys (passing score: 360/600). |
Yanyu Diao; Mengyuan Wu; Jingwen Xu; Yifeng Pan; | JMIR Human Factors | 2025-12-16 |
| 258 | Internal Reasoning Vs. External Control: A Thermodynamic Analysis of Sycophancy in Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Large Language Models frequently exhibit sycophancy, prioritizing user agreeableness over correctness. We investigate whether this requires external regulation or can be mitigated by internal reasoning alone. |
Edward Y. Chang; | arxiv-cs.CL | 2025-12-16 |
| 259 | OUSAC: Optimized Guidance Scheduling with Adaptive Caching for DiT Acceleration Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present OUSAC (Optimized gUidance Scheduling with Adaptive Caching), a framework that accelerates diffusion transformers (DiT) through systematic optimization. |
Ruitong Sun; Tianze Yang; Wei Niu; Jin Sun; | arxiv-cs.CV | 2025-12-16 |
| 260 | Prompt Repetition Improves Non-Reasoning LLMs Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: When not using reasoning, repeating the input prompt improves performance for popular models (Gemini, GPT, Claude, and Deepseek) without increasing the number of generated tokens … |
Yaniv Leviathan; Matan Kalman; Yossi Matias; | arxiv-cs.LG | 2025-12-16 |
| 261 | Inflation Attitudes of Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper investigates the ability of Large Language Models (LLMs), specifically GPT-3.5-turbo (GPT), to form inflation perceptions and expectations based on macroeconomic price signals. |
Nikoleta Anesti; Edward Hill; Andreas Joseph; | arxiv-cs.CL | 2025-12-16 |
| 262 | Towards Nepali-language LLMs: Efficient GPT Training with A Nepali BPE Tokenizer Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study presents a GPT-2-based Nepali language model trained using several training strategies inspired by GPT-3, including optimized learning rate schedules, batch scaling, and architectural refinements. |
Adarsha Shrestha; Basanta Pokharel; Binit Shrestha; Smriti Adhikari; Dinesh Gothe; | arxiv-cs.CL | 2025-12-16 |
| 263 | The Semantic Illusion: Certified Limits of Embedding-Based Hallucination Detection in RAG Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We apply conformal prediction to hallucination detection, providing finite-sample coverage guarantees that enable precise quantification of detection capabilities. |
Debu Sinha; | arxiv-cs.LG | 2025-12-16 |
| 264 | Adapter‐Regularised Continual Learning for Dynamic Financial Sentiment Encoding in Multi‐Modal Market Fusion Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: ABSTRACT We propose an adapter‐regularised continual learning framework for dynamic financial sentiment encoding, addressing the dual challenge of retaining long‐term domain knowledge while adapting to transient market sentiment patterns. |
Zihe Song; Renke Huang; Aiqi Li; Aoran Shen; Heng Chen; | Expert Systems | 2025-12-15 |
| 265 | Fake News Detection Using Albert-base-v2 Transformer and CNN-BiLSTM Architectures: A Comparative Analysis of Transformer-Based and Deep Learning Approaches Related Papers Related Patents Related Grants Related Venues Related Experts View Save |
Chi Zhang; | Informatica | 2025-12-15 |
| 266 | Detecting Emotion Drift in Mental Health Text Using Pre-Trained Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study investigates emotion drift: the change in emotional state across a single text, within mental health-related messages. |
Shibani Sankpal; | arxiv-cs.CL | 2025-12-15 |
| 267 | Comparative Evaluation of ChatGPT and Gemini in Detecting External Apical Root Resorption on Panoramic Radiographs of Orthodontic Patients Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Abstract Purpose This study aimed to evaluate the performance of large language models (LLMs), specifically GPT-4o and Gemini 2 Flash, in identifying external apical root resorption (EARR) on panoramic radiographs of orthodontic patients using a standardized prompt. Methods This comparative observational diagnostic study included 52 cropped tooth images obtained from panoramic radiographs of healthy individuals after orthodontic treatment. |
ALLAN ABUABARA et. al. | Journal of Orofacial Orthopedics / Fortschritte der … | 2025-12-15 |
| 268 | Decoding Human and AI Persuasion in National College Debate: Analyzing Prepared Arguments Through Aristotle’s Rhetorical Principles Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To better support students in preparing for debates, this study explores the potential of leveraging artificial intelligence to generate effective arguments. |
Mengqian Wu; Jiayi Zhang; Raymond Z. Zhang; | arxiv-cs.HC | 2025-12-14 |
| 269 | Does Tone Change The Answer? Evaluating Prompt Politeness Effects on Modern LLMs: GPT, Gemini, LLaMA Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we propose a systematic evaluation framework to examine how interaction tone affects model accuracy and apply it to three recently released and widely available LLMs: GPT-4o mini (OpenAI), Gemini 2.0 Flash (Google DeepMind), and Llama 4 Scout (Meta). |
Hanyu Cai; Binqi Shen; Lier Jin; Lan Hu; Xiaojing Fan; | arxiv-cs.CL | 2025-12-14 |
| 270 | The American Ghost in The Machine: How Language Models Align Culturally and The Effects of Cultural Prompting Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This work, using the VSM13 International Survey and Hofstede’s cultural dimensions, identifies the cultural alignment of popular LLMs (DeepSeek-V3, V3.1, GPT-5, GPT-4.1, GPT-4, Claude Opus 4, Llama 3.1, and Mistral Large). |
James Luther; Donald Brown; | arxiv-cs.CL | 2025-12-13 |
| 271 | Large Language Newsvendor: Decision Biases and Cognitive Mechanisms Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Problem definition: Although large language models (LLMs) are increasingly integrated into business decision making, their potential to replicate and even amplify human cognitive biases cautions a significant, yet not well-understood, risk. |
Jifei Liu; Zhi Chen; Yuanguang Zhong; | arxiv-cs.AI | 2025-12-13 |
| 272 | Can Graphs Improve Tabular Foundation Models? Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Concretely, we introduce {BOLERO}, a lightweight, static bipartite graph head that augments {RoBERTa-Tab} (a RoBERTa-style tabular backbone pretrained with masked-token prediction.) |
Franck Le; Keith Grueneberg; Erich Nahum; Vadim Sheinin; | arxiv-cs.LG | 2025-12-13 |
| 273 | Can GPT Replace Human Raters? Validity and Reliability of Machine-generated Norms for Metaphors Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Here, we present the first assessment of the validity and reliability of ratings of metaphors on familiarity, comprehensibility, and imageability, generated by three GPT models for a total of 687 items gathered from the Italian Figurative Archive and three English studies. |
Veronica Mangiaterra; Hamad Al-Azary; Chiara Barattieri di San Pietro; Paolo Canal; Valentina Bambini; | arxiv-cs.CL | 2025-12-13 |
| 274 | NagaNLP: Bootstrapping NLP for Low-Resource Nagamese Creole with Human-in-the-Loop Synthetic Data Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper introduces NagaNLP, a comprehensive open-source toolkit for Nagamese, bootstrapped through a novel methodology that relies on LLM-driven but human-validated synthetic data generation. |
Agniva Maiti; Manya Pandey; Murari Mandal; | arxiv-cs.CL | 2025-12-13 |
| 275 | Unveiling User Perceptions in The Generative AI Era: A Sentiment-Driven Evaluation of AI Educational Apps’ Role in Digital Transformation of E-Teaching Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study performs a sentiment-driven evaluation of user reviews from top AI ed-apps on the Google Play Store to assess efficacy, challenges, and pedagogical implications. |
Adeleh Mazaherian; Erfan Nourbakhsh; | arxiv-cs.CY | 2025-12-12 |
| 276 | Surveillance Video-Based Traffic Accident Detection Using Transformer Architecture Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Utilizing the curated dataset, we propose an accident detection model based on a transformer architecture using pre-extracted spatial video features. |
Tanu Singh; Pranamesh Chakraborty; Long T. Truong; | arxiv-cs.CV | 2025-12-12 |
| 277 | How Much Data in Low-resource Indian Languages Is Sufficient’ for Transfer Learning: A Comparative Study for POS Annotation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The study is conducted with Hindi as the high-resource language and the three related languages – Magahi, Bhojpuri and Braj – as extremely low-resource languages. |
Mohit Raj; Ritesh Kumar; | ACM Transactions on Asian and Low-Resource Language … | 2025-12-12 |
| 278 | ChatGPT and Reference Intervals: A Comparative Analysis of Repeatability in GPT-3.5 Turbo, GPT-4, and GPT-4o Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, their ability to generate consistent and clinically reliable reference intervals—particularly in the absence of contextual clinical information—remains uncertain. Method This cross-sectional study evaluated whether three versions of ChatGPT (GPT-3.5-Turbo, GPT-4, GPT-4o) maintain repeatable reference-interval outputs when the prompt intentionally omits the interval, using reference interval variability as a stress-test for model consistency. |
Annika Meyer; Edgar Schömig; Thomas Streichert; | Frontiers in Artificial Intelligence | 2025-12-12 |
| 279 | Enhancing Next-Generation Language Models with Knowledge Graphs: Extending Claude, Mistral IA, and GPT-4 Via KG-BERT Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Large language models (LLMs) like Claude, Mistral IA, and GPT-4 excel in NLP but lack structured knowledge, leading to factual inconsistencies. We address this by integrating Knowledge Graphs (KGs) via KG-BERT to enhance grounding and reasoning. |
Nour El Houda Ben Chaabene; Hamza Hammami; | arxiv-cs.CL | 2025-12-11 |
| 280 | An AI-Driven Product Recommendation Framework Integrating Collaborative Filtering and BERT-Based NLP Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Furthermore, current deep learning-based models like Bert4Rec or composite methods like J-NCFc continue to have high prediction errors and poor ranking accuracy. To fill these voids, this paper introduces a new CF+BERT model that incorporates collaborative filtering with contextualized review representations obtained from BERT. |
Ashrf Althbiti; | Journal of Multiscale Modelling | 2025-12-11 |
| 281 | LabelFusion: Learning to Fuse LLMs and Transformer Classifiers for Robust Text Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The package provides a simple high-level interface (AutoFusionClassifier) that trains the full pipeline end-to-end with minimal configuration, and a flexible API for advanced users. |
Michael Schlee; Christoph Weisser; Timo Kivimäki; Melchizedek Mashiku; Benjamin Saefken; | arxiv-cs.CL | 2025-12-11 |
| 282 | UrbanAI 2025 Challenge: Linear Vs Transformer Models for Long-Horizon Exogenous Temperature Forecasting Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We study long-horizon exogenous-only temperature forecasting – a challenging univariate setting where only the past values of the indoor temperature are used for prediction – using linear and Transformer-family models. |
Ruslan Gokhman; | arxiv-cs.LG | 2025-12-11 |
| 283 | Graph-augmented Transformer Ensemble Framework for Robust and Scalable Fake News Detection in Social Media Ecosystems Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we present a new hybrid model named Graph-Augmented Transformer Ensemble (GETE) for efficient and scalable fake news detection. |
CHANCHAL KUMAR et. al. | Scientific Reports | 2025-12-11 |
| 284 | SparseSwaps: Tractable LLM Pruning Mask Refinement at Scale Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we demonstrate that the mask selection problem can be made drastically more tractable at LLM scale. |
Max Zimmer; Christophe Roux; Moritz Wagner; Deborah Hendrych; Sebastian Pokutta; | arxiv-cs.LG | 2025-12-11 |
| 285 | COMPARE: Clinical Optimization with Modular Planning and Assessment Via RAG-Enhanced AI-OCT: Superior Decision Support for Percutaneous Coronary Intervention Compared to ChatGPT-5 and Junior Operators Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Subgroup analysis confirmed CA-GPT’s robust performance advantage in complex scenarios. |
WEI FANG et. al. | arxiv-cs.AI | 2025-12-11 |
| 286 | From Lab to Reality: A Practical Evaluation of Deep Learning Models and LLMs for Vulnerability Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this study, we systematically evaluate two representative DL models-ReVeal and LineVul-across four representative datasets: Juliet, Devign, BigVul, and ICVul. |
Chaomeng Lu; Bert Lagaisse; | arxiv-cs.CR | 2025-12-11 |
| 287 | LLM-Based Support for Diabetes Diagnosis: Opportunities, Scenarios, and Challenges with GPT-5 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study evaluates GPT-5, the latest generative pretrained transformer, using a simulation framework built entirely on synthetic cases aligned with ADA Standards of Care 2025 and inspired by public datasets including NHANES, Pima Indians, EyePACS, and MIMIC-IV. |
Gaurav Kumar Gupta; Nirajan Acharya; Pranal Pande; | International Journal of Modern Developments in Engineering … | 2025-12-11 |
| 288 | AI ‐Driven Intelligent Feedback System for Enhancing Self‐Assessment Accuracy in Higher Education Writing Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study introduces and evaluates an AI‐driven intelligent feedback system aimed at promoting sustainable and inclusive practices in higher education. |
Shih‐Yhe Chen; Wei‐Cheng Chen; | Expert Systems | 2025-12-11 |
| 289 | Explainable Multilingual and Multimodal Fake-news Detection: Toward Robust and Trustworthy AI for Combating Misinformation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study introduces two key innovations: (i) a new multilingual–multimodal dataset of 74,000 news articles in Hindi, Gujarati, Marathi, Telugu, and English with paired images, and (ii) Hybrid Explainable Multimodal Transformer Fake (HEMT-Fake) that integrates text, image, and relational signals with hierarchical explainability. |
ROHINI JADHAV et. al. | Frontiers in Artificial Intelligence | 2025-12-10 |
| 290 | DeepSeek’s WEIRD Behavior: The Cultural Alignment of Large Language Models and The Effects of Prompt Language and Cultural Prompting Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: As this field grows, the cultural alignment of these human-like agents becomes an important field of study. Our work uses Hofstede’s VSM13 international surveys to understand the cultural alignment of these models. |
James Luther; Donald Brown; | arxiv-cs.CL | 2025-12-10 |
| 291 | Linear Socio-demographic Representations Emerge in Large Language Models from Indirect Cues Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We investigate how LLMs encode sociodemographic attributes of human conversational partners inferred from indirect cues such as names and occupations. |
Paul Bouchaud; Pedro Ramaciotti; | arxiv-cs.AI | 2025-12-10 |
| 292 | A Comprehensive Review of Machine Learning and Deep Learning Approaches for Fake News Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This review paper presents a comprehensive survey of machine learning (ML), deep learning (DL), and transformer-based approaches designed for identifying misleading or deceptive content across digital platforms. |
Prof. Sarwesh Site; Shahbaz Akhtar; | International Journal of Scientific Research in Engineering … | 2025-12-10 |
| 293 | Automatic Essay Scoring and Feedback Generation in Basque Language Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper introduces the first publicly available dataset for Automatic Essay Scoring (AES) and feedback generation in Basque, targeting the CEFR C1 proficiency level. |
Ekhi Azurmendi; Xabier Arregi; Oier Lopez de Lacalle; | arxiv-cs.CL | 2025-12-09 |
| 294 | Is GPT-OSS All You Need? Benchmarking Large Language Models for Financial Intelligence and The Surprising Efficiency Paradox Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce novel efficiency metrics that capture the trade-off between model performance and resource utilization, providing critical insights for deployment decisions in production environments. |
Ziqian Bi; Danyang Zhang; Junhao Song; Chiung-Yi Tseng; | arxiv-cs.LG | 2025-12-09 |
| 295 | GThinker – A Chatbot Using AI Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Abstract—This paper presents the development of GThinker, an intelligent chatbot designed using Natural Language Processing (NLP) and advanced AI models to deliver human-like, context-aware, and emotionally adaptive interactions. |
R Harshith Raj; Dr. Sheethal Aji Mani; Aditya N; Darshan V; Madhu S; | International Journal of Scientific Research in Engineering … | 2025-12-09 |
| 296 | Integrating Multimodal Clinical Data to Predict Intravenous (IV) Fluid Utilization: A Comparative Analysis of Natural Language Processing Techniques Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Methods We analyzed a large dataset from the National Hospital Ambulatory Medical Care Survey—Emergency Department (NHAMCS-ED, n = 13,115), comprising both structured patient demographics and clinical variables, alongside unstructured chief complaints. |
Hairong Wang; Haipeng Ling; Xingyu Zhang; | PeerJ Computer Science | 2025-12-09 |
| 297 | LLMs for Analog Circuit Design Continuum (ACDC) Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we investigate the applicability and consistency of LLMs for analog circuit design — a task requiring domain-specific reasoning, adherence to physical constraints, and structured representations — focusing on AI-assisted design where humans remain in the loop. |
Yasaman Esfandiari; Jocelyn Rego; Austin Meyer; Jonathan Gallagher; Mia Levy; | arxiv-cs.LG | 2025-12-09 |
| 298 | Systematic Evaluation of ChatGPT Performance in Providing Renewable Energy Information Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The renewable energy field is a prominent field, which aims to explore alternative sources of energy that are more affordable and effective. In this study, we examine how accurate ChatGPT is when it comes to providing general, non-technical information on renewable energy compared to human experts in this field. |
Mohammed S. Ibrahim; Ahmed J. Aljaaf; Mohammed Al-khafajiy; Ahmed Adil Nafea; Nor Samsiah Sani; | PeerJ Computer Science | 2025-12-08 |
| 299 | Securing Local LLMs for Academic Research: A Human-system Integration Analysis and Evolution of TAUCHI-GPT Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper introduces TAUCHI-GPT, a novel, open-source AI assistant whose evolution informs our analysis. |
AHMED FAROOQ et. al. | Human-Intelligent Systems Integration | 2025-12-08 |
| 300 | Classifying Human Vs. AI Text with Machine Learning and Explainable Transformer Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study presents a comprehensive framework for distinguishing between human-written and GPT-generated text using a combination of machine learning, sequential deep learning, and transformer-based models. |
ADVEN MASIH et. al. | Scientific Reports | 2025-12-08 |
| 301 | KV-CAR: KV Cache Compression Using Autoencoders and KV Reuse in Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The KV cache grows with sequence length and embedding dimension, often exceeding the memory footprint of the model itself and limiting achievable batch sizes and context windows. To address this challenge, we present KV CAR, a unified and architecture agnostic framework that significantly reduces KV cache storage while maintaining model fidelity. |
Sourjya Roy; Shrihari Sridharan; Surya Selvam; Anand Raghunathan; | arxiv-cs.LG | 2025-12-07 |
| 302 | An Exploratory Semantic Analysis of Age-Related Stereotypes in OpenAI’s GPT 4o Model Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Abstract Background and Objectives Generative artificial intelligence, particularly large language models (LLMs), is increasingly used to navigate information, potentially shaping users’ perceptions of different social groups. |
Wan Hong; Moon Choi; | The Gerontologist | 2025-12-07 |
| 303 | Mechanistic Interpretability of GPT-2: Lexical and Contextual Layers in Sentiment Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present a mechanistic interpretability study of GPT-2 that causally examines how sentiment information is processed across its transformer layers. |
Amartya Hatua; | arxiv-cs.CL | 2025-12-07 |
| 304 | PrivLLMSwarm: Privacy-Preserving LLM-Driven UAV Swarms for Secure IoT Surveillance Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This work introduces PrivLLMSwarm, a privacy-preserving framework that performs secure LLM inference for UAV swarm coordination through Secure Multi-Party Computation (MPC). |
Jifar Wakuma Ayana; Huang Qiming; | arxiv-cs.CR | 2025-12-07 |
| 305 | Deep Reinforcement Learning for Phishing Detection with Transformer-Based Semantic Features Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study proposes a Quantile Regression Deep Q-Network (QR-DQN) approach that integrates RoBERTa semantic embeddings with handcrafted lexical features to enhance phishing detection while accounting for uncertainties. |
Aseer Al Faisal; | arxiv-cs.LG | 2025-12-07 |
| 306 | Transformer-Based Sentiment Analysis on Amazon Reviews Using Kaggle Dataset Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents a comprehensive study of sentiment classification on a large Amazon Reviews dataset from Kaggle, containing millions of reviews with star ratings, by fine-tuning state-of-the-art transformer models. |
Shwetaba B. Chauhan; Japan M. Mavani; | International Journal of Innovative Science and Research … | 2025-12-06 |
| 307 | Chemistry Integrated Language Model Using Hierarchical Molecular Representation for Polymer Informatics Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce CI-LLM (Chemically Informed Language Model), a framework combining HAPPY (Hierarchically Abstracted rePeat unit of PolYmer), which encodes chemical substructures as tokens, with numerical descriptors within transformer architectures. |
Jihun Ahn; Gabriella Pasya Irianti; Vikram Thapar; Su-Mi Hur; | arxiv-cs.LG | 2025-12-06 |
| 308 | Automated Identification of Incidentalomas Requiring Follow-Up: A Multi-Anatomy Evaluation of LLM-Based and Supervised Approaches Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduced a novel inference strategy using lesion-tagged inputs and anatomy-aware prompting to ground model reasoning. |
NAMU PARK et. al. | arxiv-cs.CL | 2025-12-05 |
| 309 | Leveraging Large Language Models to Detect Academic Anxiety in Indonesian English for Specific Purposes Students Through Reflective Writing Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study investigates the capacity of Large Language Models to identify academic anxiety in reflective writing produced by English for Specific Purposes students from Indonesia. |
Khoirul Anwar; Bambang Harmanto; | International Journal of Learning, Teaching and Educational … | 2025-12-05 |
| 310 | BERTO: An Adaptive BERT-based Network Time Series Predictor with Operator Preferences in Natural Language Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce BERTO, a BERT-based framework for traffic prediction and energy optimization in cellular networks. |
Nitin Priyadarshini Shankar; Vaibhav Singh; Sheetal Kalyani; Christian Maciocco; | arxiv-cs.LG | 2025-12-05 |
| 311 | Enhancing Dementia and Cognitive Decline Detection with Large Language Models and Speech Representation Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study describes our submission to the PROCESS Signal Processing Grand Challenge (ICASSP 2025), which tasked participants with predicting cognitive decline from speech samples. |
Karol Chlasta; Piotr Struzik; Grzegorz M. Wójcik; | Frontiers in Neuroinformatics | 2025-12-05 |
| 312 | Capturing Classic Authorial Style in Long-Form Story Generation with GRPO Fine-Tuning Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we present a training framework for style-conditioned story generation using Group Relative Policy Optimization (GRPO) and a custom multi-reward setup. |
Jinlong Liu; Mohammed Bahja; Venelin Kovatchev; Mark Lee; | arxiv-cs.CL | 2025-12-05 |
| 313 | Robust Sentiment Analysis Through Bayesian Dropout-Enhanced RoBERTa-LSTM Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper introduces RoBERTa-LSTM-Drop, a hybrid architecture that combines RoBERTa embeddings with bidirectional LSTM layers and integrates Bayesian Dropout to capture uncertainty through Monte Carlo sampling while acting as an effective regulariser. |
Soufien Jaffali; | BRAIN. Broad Research in Artificial Intelligence and … | 2025-12-05 |
| 314 | Hate Speech Identification in Formal and Informal Social Media Text Using RoBERTa-Base and XLM-RoBERTa-Base Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this study, we present the performance comparison of two transformer-based models, RoBERTa-Base and XLM-RoBERTa-Base, for hate speech identification in formal (English) and informal (Roman Urdu and mixed English-Roman Urdu) text. |
Husnain Saleem; Muhammad Javed; Junaid Khan; | BRAIN. Broad Research in Artificial Intelligence and … | 2025-12-05 |
| 315 | AGF-HAM: Adaptive Gated Fusion Hierarchical Attention Model for Explainable Sentiment Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This research paper presents a new hybrid model, HAM (Hybrid Attention-based Model), a Transformer-based contextual embedding model combined with deep sequential modeling and multi-layer explainability. |
Mahander Kumar; Lal Khan; Mohammad Zubair Khan; Amel Ali Alhussan; | Mathematics | 2025-12-05 |
| 316 | Sustainable Urban Mobility: Leveraging Generative AI for Symmetry-Aware Traffic Light Optimization Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study introduces a symmetry-aware generative optimization framework that leverages Generative Artificial Intelligence (GAI) to balance both dimensions. |
Pedro C. Santana-Mancilla; Antonio Guerrero-Ibáñez; Juan Contreras-Castillo; Jesús García-Mancilla; Luis Anido-Rifón; | Symmetry | 2025-12-04 |
| 317 | KV Cache Recycling to Expand Usable Context Capacity in Low Parameter LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Whether attention key value (KV) states computed for one prompt for a small LLM can be reused to accelerate inference on a new similar prompt, giving an increase to the space to its context memory using an approach called token recycling. |
Prashant Pandey; | arxiv-cs.LG | 2025-12-04 |
| 318 | Towards Improved Fake News Detection Using A Hybrid RoBERTa and Metadata Enhanced XGBoost Model Related Papers Related Patents Related Grants Related Venues Related Experts View Save |
ARMUGHAN ALI et. al. | Scientific Reports | 2025-12-04 |
| 319 | Fusing Semantic and Structural Features for Code Error Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Nevertheless, their efficacy could be further improved by addressing the inherent weakness in handling structural code dependencies. In response to this, we introduce a novel model that integrates the semantic comprehension power of RoBERTa with the structural learning strength of Graph Neural Networks. |
Yiwen Zhang; Wei Liu; Fazhong Jiang; Jiquan Ma; Jingtai Cao; | Entropy | 2025-12-04 |
| 320 | Multi-Modal Opinion Integration for Financial Sentiment Analysis Using Cross-Modal Attention Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper proposes an end-to-end deep learning framework that integrates two distinct modalities of financial opinions: recency modality (timely opinions) and popularity modality (trending opinions), through a novel cross-modal attention mechanism specifically designed for financial sentiment analysis. |
Yujing Liu; Chen Yang; | arxiv-cs.LG | 2025-12-03 |
| 321 | Hamisfera: Sistem Rekomendasi Progresi Chord Berbasis Sentimen Lirik Melalui Studi Komparatif Arsitektur Transformer Dan Mixture of Experts Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Abstrak – Proses penciptaan lagu sering kali memerlukan penyelarasan antara nuansa emosional lirik dengan harmoni musik yang tepat. Namun, penerjemahan sentimen lirik menjadi … |
Fara Daud Ibra; Muhammad Fachrie; | Jurnal Informatika dan Multimedia | 2025-12-03 |
| 322 | GRASP: GRouped Activation Shared Parameterization for Parameter-Efficient Fine-Tuning and Robust Inference of Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce GRASP – GRouped Activation Shared Parameterization – a lightweight PEFT framework that partitions the D-dimensional token representations of selected layers into K << D groups and learns a shared scaling and shifting vector for each group. |
Malyaban Bal; Abhronil Sengupta; | arxiv-cs.LG | 2025-12-03 |
| 323 | Pianist Transformer: Towards Expressive Piano Performance Rendering Via Scalable Self-Supervised Pre-Training Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Existing methods for expressive music performance rendering rely on supervised learning over small labeled datasets, which limits scaling of both data volume and model size, despite the availability of vast unlabeled music, as in vision and language. To address this gap, we introduce Pianist Transformer, with four key contributions: 1) a unified Musical Instrument Digital Interface (MIDI) data representation for learning the shared principles of musical structure and expression without explicit annotation; 2) an efficient asymmetric architecture, enabling longer contexts and faster inference without sacrificing rendering quality; 3) a self-supervised pre-training pipeline with 10B tokens and 135M-parameter model, unlocking data and model scaling advantages for expressive performance rendering; 4) a state-of-the-art performance model, which achieves strong objective metrics and human-level subjective ratings. |
HONG-JIE YOU et. al. | arxiv-cs.SD | 2025-12-02 |
| 324 | Imaging-based Transformer Model Predicts Early Therapy Response in Advanced Nasopharyngeal Carcinoma: A Dual-center Study Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: A 2.5D approach integrated adjacent tumor sections into a transfer learning framework, leading to three predictive models: Clinical, Transformer, and Combined. |
KEXIN SHI et. al. | Insights into Imaging | 2025-12-02 |
| 325 | Dual LoRA: Enhancing LoRA with Magnitude and Direction Updates Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we propose a novel method called Dual LoRA to improve the performance by incorporating an inductive bias into the original LoRA. |
YIXING XU et. al. | arxiv-cs.CL | 2025-12-02 |
| 326 | Artificial Intelligence for Employee Engagement and Well-Being: A Review of Digital Tools, Psychometric Measures and Workforce Sentiment Datasets in Modern HR Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper assesses empirical and conceptual evidence from 2015–2025 across three interconnected domains of modern HR analytics: AI-driven digital engagement and well-being tools, psychometric measures embedded in AI systems, and real-world workforce sentiment datasets used for model development and validation. |
Francis Dumbili; Onyinye Uzoka; Seun Adeniran; Mercy Afreh; | World Journal of Advanced Research and Reviews | 2025-12-02 |
| 327 | Object Counting with GPT-4o and GPT-5: A Comparative Study Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work we aim to leverage the visual capabilities of two multi-modal LLMs, GPT-4o and GPT-5, to perform object counting in a zero-shot manner using only textual prompts. |
Richard Füzesséry; Kaziwa Saleh; Sándor Szénási; Zoltán Vámossy; | arxiv-cs.CV | 2025-12-02 |
| 328 | Bangla Hate Speech Classification with Fine-tuned Transformer Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we study Subtask 1A and Subtask 1B of the BLP 2025 Shared Task on hate speech detection. |
Yalda Keivan Jafari; Krishno Dey; | arxiv-cs.CL | 2025-12-02 |
| 329 | Enhancing Recommendation Systems with Autoencoder-SVD and Transformer-Based Summarization: A Sentiment-Aware Approach Using GPT-2 and VADER Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper proposes a novel approach to improve recommendation accuracy by integrating Autoencoder-SVD with language model-based summarization. |
Muhi Saadi Rahdi; Farsad Zamani Boroujeni; Aladdin Abdulhassan; Mehdi Akbari Kopayei; Keyvan Mohebbi; | Qubahan Academic Journal | 2025-12-02 |
| 330 | SPECTRE: Computational Methods in Natural Language Processing for Automated Hardware Trojan Insertion Using Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Experts Stealthy Processor Exploitation and Concealment Through Reconfigurable Elements (SPECTRE) is the new framework proposed in this paper to use the computational methods of Natural Language Processing (NLP) to automate the addition of Hardware Trojans (HTs) to the complex hardware design. |
Moneer Alshaikh; Rashid Amin; Sajid Mehmood; Faisal S. Alsubaei; | Contemporary Mathematics | 2025-12-02 |
| 331 | Idea-Gated Transformers: Enforcing Semantic Coherence Via Differentiable Vocabulary Pruning Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we introduce the Idea-Gated Transformer, a novel architecture that separates semantic planning from syntactic generation. |
Darshan Fofadiya; | arxiv-cs.CL | 2025-12-02 |
| 332 | What Signals Really Matter for Misinformation Tasks? Evaluating Fake-News Detection and Virality Prediction Under Real-World Constraints Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present an evaluation-driven study of two practical tasks regarding online misinformation: (i) fake-news detection and (ii) virality prediction in the context of operational settings, with the necessity for rapid reaction. |
Francesco Paolo Savatteri; Chahan Vidal-Gorène; Florian Cafiero; | arxiv-cs.CL | 2025-12-02 |
| 333 | DETAIL Matters: Measuring The Impact of Prompt Specificity on Reasoning in Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper introduces DETAIL, a framework for evaluating LLM performance across varying levels of prompt specificity. |
Olivia Kim; | arxiv-cs.CL | 2025-12-01 |
| 334 | Enhancing Task Prioritization in Software Development Issues Tracking System Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper investigates the potential of automated issue priority classification using state‐of‐the‐art Transformer models to alleviate this burden. We evaluate the performance of models like BERT, DeBERTa, and ModernBERT, comparing them against general large language models (LLMs) such as GPT‐3.5, Qwen2.5‐3B and Llama‐3.2‐3B, using curated datasets derived from public Jira and GitHub repositories. |
Karthik Shivashankar; Kristian Marison Haugerud; Antonio Martini; | Journal of Software: Evolution and Process | 2025-12-01 |
| 335 | A Large Language Model for Clinical Outcome Adjudication from Telephone Follow-up Interviews: A Secondary Analysis of A Multicenter Randomized Clinical Trial Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Here, we show that a domain-specific large language model (Fu-LLM) effectively automates the preadjudication of key clinical events—including death, hospitalization, and medication use—based on 1,046 vignettes of follow-up telephone interviews conducted across three centers in a randomized clinical trial (China CT-FFR Study 3). |
ZHAO SHI et. al. | Nature Communications | 2025-12-01 |
| 336 | Testing Transformer Learnability on The Arithmetic Sequence of Rooted Trees Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We study whether a Large Language Model can learn the deterministic sequence of trees generated by the iterated prime factorization of the natural numbers. |
Alessandro Breccia; Federica Gerace; Marco Lippi; Gabriele Sicuro; Pierluigi Contucci; | arxiv-cs.AI | 2025-12-01 |
| 337 | Handwritten Text Recognition for Low Resource Languages Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose a ViT-Transformer Decoder-LM architecture for handwritten text recognition, where a Vision Transformer (ViT) extracts visual features, a Transformer decoder generates text sequences, and a pre-trained language model (LM) refines the output to improve accuracy, fluency, and coherence. |
Sayantan Dey; Alireza Alaei; Partha Pratim Roy; | arxiv-cs.CV | 2025-12-01 |
| 338 | MicroProbe: Efficient Reliability Assessment for Foundation Models with Minimal Data Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce microprobe, a novel approach that achieves comprehensive reliability assessment using only 100 strategically selected probe examples. |
Aayam Bansal; Ishaan Gangwani; | arxiv-cs.AI | 2025-11-30 |
| 339 | Advancing Academic Chatbots: Evaluation of Non Traditional Outputs Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We implemented a prototype combining Meta’s LLaMA 3 70B open weight and OpenAI’s GPT 4o mini API based. |
Nicole Favero; Francesca Salute; Daniel Hardt; | arxiv-cs.CL | 2025-11-30 |
| 340 | LLM-as-a-Judge for Scalable Test Coverage Evaluation: Accuracy, Operational Reliability, and Cost Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present LLM-as-a-Judge (LAJ), a production-ready, rubric-driven framework for evaluating Gherkin acceptance tests with structured JSON outputs. |
Donghao Huang; Shila Chew; Anna Dutkiewicz; Zhaoxia Wang; | arxiv-cs.SE | 2025-11-30 |
| 341 | Generalized Graph Transformer Variational Autoencoder Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we propose the Generalized Graph Transformer Variational Autoencoder (GGT-VAE). |
Siddhant Karki; | arxiv-cs.LG | 2025-11-29 |
| 342 | Financial Text Classification Based On RLoRA Finetuning On Qwen3-8B Model Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we assess the performance of the large language model Qwen3-8B on both tasks. |
Zhiming Lian; | arxiv-cs.LG | 2025-11-29 |
| 343 | Pooling Attention: Evaluating Pretrained Transformer Embeddings for Deception Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper investigates fake news detection as a downstream evaluation of Transformer representations, benchmarking encoder-only and decoder-only pre-trained models (BERT, GPT-2, Transformer-XL) as frozen embedders paired with lightweight classifiers. |
Sumit Mamtani; Abhijeet Bhure; | arxiv-cs.CL | 2025-11-28 |
| 344 | Tourism Question Answer System in Indian Language Using Domain-Adapted Foundation Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, a dataset comprising 7,715 Hindi QA pairs pertaining to Varanasi tourism was constructed and subsequently augmented with 27,455 pairs generated via Llama zero-shot prompting. |
Praveen Gatla; Nikita Kanwar; Gouri Sahoo; Rajesh Kumar Mundotiya; | arxiv-cs.CL | 2025-11-28 |
| 345 | Tree Matching Networks for Natural Language Inference: Parameter-Efficient Semantic Understanding Via Dependency Parse Trees Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Explicit structural representations significantly outperform sequence-based models at comparable scales, but current aggregation methods limit scalability. We propose multi-headed attention aggregation to address this limitation. |
Jason Lunder; | arxiv-cs.CL | 2025-11-28 |
| 346 | Development of A High-Performance Regenerative Shock Absorber Utilizing Helical Gears for Efficient Energy Harvesting and Range Extension in Electric Vehicles Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This manuscript proposes a combined approach for an efficient regenerative absorber related to a twin helical-gear for range-extended electric vehicles (EVs). |
V.V.M. Swamy; S. Vidyasagar; | Journal of Circuits, Systems and Computers | 2025-11-28 |
| 347 | Challenges of Heterogeneity in Big Data: A Comparative Study of Classification in Large-Scale Structured and Unstructured Domains Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This work provides a unified framework for algorithm selection based on data nature and infrastructure constraints. |
González Trigueros Jesús Eduardo; Alonso Sánchez Alejandro; Muñoz Rivera Emilio; Peñarán Prieto Mariana Jaqueline; Mendoza González Camila Natalia; | arxiv-cs.LG | 2025-11-28 |
| 348 | Exploring The Predictive Performance of Deep Learning for Fracturing Fluid Flowback and Shale Gas Production Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Here, we developed CNN-Transformer, a production and fluid flowback predicted system using deep learning, by integrating a convolutional neural network (CNN) and a Transformer network. |
SHASHA SUN et. al. | Scientific Reports | 2025-11-28 |
| 349 | Transformer-Driven Triple Fusion Framework for Enhanced Multimodal Author Intent Classification in Low-Resource Bangla Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Recognizing limitations in previous unimodal approaches, we systematically benchmark transformer-based language models (mBERT, DistilBERT, XLM-RoBERTa) and vision architectures (ViT, Swin, SwiftFormer, ResNet, DenseNet, MobileNet), utilizing the Uddessho dataset of 3,048 posts spanning six practical intent categories. We introduce a novel intermediate fusion strategy that significantly outperforms early and late fusion on this task. |
Ariful Islam; Tanvir Mahmud; Md Rifat Hossen; | arxiv-cs.LG | 2025-11-28 |
| 350 | MCP Vs RAG Vs NLWeb Vs HTML: A Comparison of The Effectiveness and Efficiency of Different Agent Interfaces to The Web (Technical Report) Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, no prior work has compared these four architectures within a single controlled environment using identical tasks. To address this gap, we introduce a testbed consisting of four simulated e-shops, each offering its products via HTML, MCP, and NLWeb interfaces. |
Aaron Steiner; Ralph Peeters; Christian Bizer; | arxiv-cs.CL | 2025-11-28 |
| 351 | A Theoretically Grounded Hybrid Ensemble for Reliable Detection of LLM-Generated Text Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose a theoretically grounded hybrid ensemble that systematically fuses three complementary detection paradigms: (i) a RoBERTa-based transformer classifier for deep semantic feature extraction, (ii) a GPT-2-based probabilistic detector using perturbation-induced likelihood curvature, and (iii) a statistical linguistic feature analyzer capturing stylometric patterns. |
Sepyan Purnama Kristanto; Lutfi Hakim; | arxiv-cs.CL | 2025-11-27 |
| 352 | Sentiment Analysis Of Shopee Product Reviews Using Distilbert Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study examines the use of DistilBERT, a lightweight transformer-based deep learning model, for sentiment classification on Shopee product reviews. |
Zahri Aksa Dautd; Aviv Yuniar Rahman; | arxiv-cs.CL | 2025-11-27 |
| 353 | Transformer and Pre-Transformer Model-Based Sentiment Prediction with Various Embeddings: A Case Study on Amazon Reviews Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study contributes to both sentiment analysis and sustainable AI by offering a scalable, entropy-aware evaluation framework that supports informed, context-sensitive model selection for practical applications. |
Ismail Duru; Ayşe Saliha Sunar; | Entropy | 2025-11-27 |
| 354 | Efficient Adaptation of Large Language Models for Sentiment Analysis: A Fine-Tuning Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study presents a systematic comparative analysis of sentiment classification on financial news headlines using two transformer architectures, Mistral-7B and GPT-2, fine-tuned with advanced adaptation techniques—Quantized Low-Rank Adaptation (QLoRA) and Low-Rank Adaptation (LoRA). |
Seda Bayat Toksöz; Gültekin Işık; | Iğdır Üniversitesi Fen Bilimleri Enstitüsü Dergisi | 2025-11-27 |
| 355 | Contextual Gating Within The Transformer Stack: Synergistic Feature Modulation for Enhanced Lyrical Classification and Calibration Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: I propose the SFL Transformer, a novel deep learning model that utilizes a Contextual Gating mechanism (an Intermediate SFL) to modulate the sequence of hidden states within the BERT encoder stack, rather than fusing features at the final output layer. |
M. A. Gameiro; | arxiv-cs.LG | 2025-11-27 |
| 356 | LC4-DViT: Land-cover Creation for Land-cover Classification with Deformable Vision Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose LC4-DViT (Land-cover Creation for Land-cover Classification with Deformable Vision Transformer), a framework that combines generative data creation with a deformation-aware Vision Transformer. |
KAI WANG et. al. | arxiv-cs.CV | 2025-11-27 |
| 357 | Using Text-Based Life Trajectories from Swedish Register Data to Predict Residential Mobility with Pretrained Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We transform large-scale Swedish register data into textual life trajectories to address two long-standing challenges in data analysis: high cardinality of categorical variables and inconsistencies in coding schemes over time. Leveraging this uniquely comprehensive population register, we convert register data from 6.9 million individuals (2001-2013) into semantically rich texts and predict individuals’ residential mobility in later years (2013-2017). |
Philipp Stark; Alexandros Sopasakis; Ola Hall; Markus Grillitsch; | arxiv-cs.LG | 2025-11-26 |
| 358 | Evaluating The Effectiveness of AI-Assisted Emotional Metadata in Enhancing The Discoverability of Literary Texts in Digital Libraries Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The research shows that discovery in digital libraries, user interaction, and search can be boosted by adding emotional metadata in digital libraries. |
Bushara Iqbal; | Social Sciences & Humanity Research Review | 2025-11-26 |
| 359 | Visualizing LLM Latent Space Geometry Through Dimensionality Reduction Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we extract, process, and visualize latent state geometries in Transformer-based language models through dimensionality reduction. |
Alex Ning; Vainateya Rangaraju; | arxiv-cs.LG | 2025-11-26 |
| 360 | SparseWorld-TC: Trajectory-Conditioned Sparse Occupancy World Model Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper introduces a novel architecture for trajectory-conditioned forecasting of future 3D scene occupancy. |
JIAYUAN DU et. al. | arxiv-cs.CV | 2025-11-26 |
| 361 | BanglaMM-Disaster: A Multimodal Transformer-Based Deep Learning Framework for Multiclass Disaster Classification in Bangla Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this study, we present BanglaMM-Disaster, an end-to-end deep learning-based multimodal framework for disaster classification in Bangla, using both textual and visual data from social media. |
Ariful Islam; Md Rifat Hossen; Md. Mahmudul Arif; Abdullah Al Noman; Md Arifur Rahman; | arxiv-cs.LG | 2025-11-26 |
| 362 | Performance of O1 Pro and GPT-4 in Self-Assessment Questions for Nephrology Board Renewal IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We compared two advanced LLMs, GPT-4 and the newly released o1 pro, on comprehensive nephrology board renewal examinations. |
Ryunosuke Noda; Chiaki Yuasa; Fumiya Kitano; Daisuke Ichikawa; Yugo Shibagaki; | Frontiers in Medicine | 2025-11-25 |
| 363 | ChatGpt Content Detection: A New Approach Using Xlm-roberta Alignment Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The challenge of separating AI-generated text from human-authored content is becoming more urgent as generative AI technologies like ChatGPT become more widely available. In this work, we address this issue by looking at both the detection of content that has been entirely generated by AI and the identification of human text that has been reworded by AI. |
MD TASNIN TANVIR et. al. | arxiv-cs.LG | 2025-11-25 |
| 364 | Comparing Alzheimer Disease Phenotype Extraction Using Rule-based Natural Language Processing, GPT-4, Phi-4, LLaMA, and DeepSeek Related Papers Related Patents Related Grants Related Venues Related Experts View Save |
INEZ Y. OH et. al. | npj Dementia | 2025-11-25 |
| 365 | HHFT: Hierarchical Heterogeneous Feature Transformer for Recommendation Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose HHFT (Hierarchical Heterogeneous Feature Transformer), a Transformer-based architecture tailored for industrial CTR prediction. |
Liren Yu; Wenming Zhang; Silu Zhou; Zhixuan Zhang; Dan Ou; | arxiv-cs.IR | 2025-11-25 |
| 366 | Building A Foundation Model for Trajectory from Scratch Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Through a concise, step-by-step, code-driven process, we demonstrate adapting GPT-2 for spatiotemporal data. |
Gaspard Merten; Mahmoud Sakr; Gilles Dejaegere; | arxiv-cs.AI | 2025-11-25 |
| 367 | Directional Optimization Asymmetry in Transformers: A Synthetic Stress Test Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Using random string mappings with tunable branching factor K, we construct forward tasks with zero conditional entropy and inverse tasks with analytically determined entropy floors. |
Mihir Sahasrabudhe; | arxiv-cs.CL | 2025-11-25 |
| 368 | DPATransLLM: Detection of Pronominal Anaphora in Turkish Sentences Using Transformer-Based, Large Language Models and Hybrid Ensemble Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, fine-tuning was performed on Transformer-based language models pre-trained on Turkish data, such as BERT and RoBERTa. |
Engin Demir; Metin Bilgin; | Applied Sciences | 2025-11-25 |
| 369 | When Data Is Scarce, Prompt Smarter… Approaches to Grammatical Error Correction in Low-Resource Settings Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: For most Indic languages, GEC remains a challenging task due to limited resources, linguistic diversity and complex morphology. In this work, we explore prompting-based approaches using state-of-the-art large language models (LLMs), such as GPT-4.1, Gemini-2.5 and LLaMA-4, combined with few-shot strategy to adapt them to low-resource settings. |
Somsubhra De; Harsh Kumar; Arun Prakash A; | arxiv-cs.CL | 2025-11-25 |
| 370 | Dissecting The Ledger: Locating and Suppressing Liar Circuits in Financial Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we propose a mechanistic approach to intrinsic hallucination detection. |
Soham Mirajkar; | arxiv-cs.CL | 2025-11-24 |
| 371 | Learning to Reason: Training LLMs with GPT-OSS or DeepSeek R1 Reasoning Traces Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we compare the performance of medium-sized LLMs on Math problems after post-training on two kinds of reasoning traces. |
Shaltiel Shmidman; Asher Fredman; Oleg Sudakov; Meriem Bendris; | arxiv-cs.CL | 2025-11-24 |
| 372 | Large Language Models Management of Complex Medication Regimens: A Case-based Evaluation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Clinicians continued LLM-recommended medications at a rate of 54.6%–67.3%, with GPT-4 having the highest rate of medication continuation among all LLMs tested (p < 0.001) and the lowest rate of life-threatening medication errors (p < 0.001). Conclusion Caution is warranted using present LLMs for medication regimens given the number of medication errors that were identified in this pilot study. |
AARON CHASE et. al. | Frontiers in Pharmacology | 2025-11-24 |
| 373 | On The Role of Hidden States of Modern Hopfield Network in Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: It has been pointed out that the state update rule of the modern Hopfield network (MHN) in the adiabatic approximation is in agreement with the self-attention layer of Transformer. In this paper, we go beyond this approximation and investigate the relationship between MHN and self-attention. |
Tsubasa Masumura; Masato Taki; | arxiv-cs.LG | 2025-11-24 |
| 374 | Scaling Item-to-Standard Alignment with Large Language Models: Accuracy, Limits, and Solutions Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Traditional human alignment reviews are accurate but slow and labor-intensive, especially across large item banks. This study examines whether Large Language Models (LLMs) can accelerate this process without sacrificing accuracy. |
Farzan Karimi-Malekabadi; Pooya Razavi; Sonya Powers; | arxiv-cs.AI | 2025-11-24 |
| 375 | Are Large Vision Language Models Truly Grounded in Medical Images? Evidence from Italian Clinical Visual Question Answering Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Large vision language models (VLMs) have achieved impressive performance on medical visual question answering benchmarks, yet their reliance on visual information remains unclear. |
FEDERICO FELIZZI et. al. | arxiv-cs.CV | 2025-11-24 |
| 376 | Intelligent Sustainability: Evaluating Transformers for Cryptocurrency Environmental Claims Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Employing design science research (DSR) methodology, we develop and empirically evaluate a novel framework comparing five state-of-the-art transformer models across multiple performance dimensions. |
Parisa Bouzari; Maria Fekete-Farkas; Zsigmond Gábor Szalay; | Information | 2025-11-24 |
| 377 | Assessing The Efficacy of Ortho GPT: A Comparative Study with Medical Students and General LLMs on Orthopedic Examination Questions Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The domain-specific approach enables performance matching or exceeding top general LLMs in orthopedics, emphasizing the importance of domain specialization for reliable, curriculum-aligned support in medical education. |
PHILIPPE FABIAN POHLMANN et. al. | Bioengineering | 2025-11-24 |
| 378 | Empathetic Cascading Networks: A Multi-Stage Prompting Technique for Reducing Social Biases in Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This report presents the Empathetic Cascading Networks (ECN) framework, a multi-stage prompting method designed to enhance the empathetic and inclusive capabilities of large language models. |
Wangjiaxuan Xin; | arxiv-cs.CL | 2025-11-23 |
| 379 | Grounded Instruction Understanding with Large Language Models: Toward Trustworthy Human-Robot Interaction Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Understanding natural language as a representational bridge between perception and action is critical for deploying autonomous robots in complex, high-risk environments. This work investigates how large language models (LLMs) can support this bridge by interpreting unconstrained human instructions in urban disaster response scenarios. |
Ekele Ogbadu; Stephanie Lukin; Cynthia Matuszek; | Proceedings of the AAAI Symposium Series | 2025-11-23 |
| 380 | From Code Foundation Models to Agents and Applications: A Comprehensive Survey and Practical Guide to Code Intelligence Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Large language models (LLMs) have fundamentally transformed automated software development by enabling direct translation of natural language descriptions into functional code, … |
JIAN YANG et. al. | ArXiv | 2025-11-23 |
| 381 | Towards Fairer AI: Multi-Agent Debiasing of LLMs With Online Evidence Retrieval Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce MADERA (Multi-Agent Debiasing with External Retrieval and Assessment), a self-contained multi-agent framework that (i) diagnoses biased chains of thought, (ii) retrieves relevant web evidence through a search agent, and (iii) iteratively rewrites reasoning until bias is eliminated. |
Mughees Ur Rehman; Saleha Muzammil; | Proceedings of the AAAI Symposium Series | 2025-11-23 |
| 382 | The Catastrophic Paradox of Human Cognitive Frameworks in Large Language Model Evaluation: A Comprehensive Empirical Analysis of The CHC-LLM Incompatibility Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose a framework for developing native machine cognition assessments that recognize the non-human nature of artificial intelligence. |
Mohan Reddy; | arxiv-cs.AI | 2025-11-23 |
| 383 | AGI Team at SHROOM-CAP: Data-Centric Approach to Multilingual Hallucination Detection Using XLM-RoBERTa Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper describes our submission to the SHROOM-CAP 2025 shared task on scientific hallucination detection across 9 languages. |
Harsh Rathva; Pruthwik Mishra; Shrikant Malviya; | arxiv-cs.CL | 2025-11-23 |
| 384 | Evaluating Large Language Models on The 2026 Korean CSAT Mathematics Exam: Measuring Mathematical Ability in A Zero-Data-Leakage Setting Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study systematically evaluated the mathematical reasoning capabilities of Large Language Models (LLMs) using the 2026 Korean College Scholastic Ability Test (CSAT) Mathematics section, ensuring a completely contamination-free evaluation environment. |
GOUN PYEON et. al. | arxiv-cs.CL | 2025-11-23 |
| 385 | Toward Trustworthy Difficulty Assessments: Large Language Models As Judges in Programming and Synthetic Tasks Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Large Language Models (LLMs) have demonstrated impressive capabilities in natural language and code generation, and are increasingly deployed as automatic judges of model outputs and learning activities. |
H. M. Shadman Tabib; Jaber Ahmed Deedar; | arxiv-cs.CL | 2025-11-23 |
| 386 | PeriodNet: Boosting The Potential of Attention Mechanism for Time Series Forecasting Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we present PeriodNet with a brand new structure to forecast univariate and multivariate time series. |
BOWEN ZHAO et. al. | arxiv-cs.LG | 2025-11-23 |
| 387 | From Reviewers’ Lens: Understanding Bug Bounty Report Invalid Reasons with LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we conduct an empirical study with the purpose of helping bug hunters understand the validity of reports. |
Jiangrui Zheng; Yingming Zhou; Ali Abdullah Ahmad; Hanqing Yao; Xueqing Liu; | arxiv-cs.SE | 2025-11-23 |
| 388 | From Code Foundation Models to Agents and Applications: A Practical Guide to Code Intelligence Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we provide a comprehensive synthesis and practical guide (a series of analytic and probing experiments) about code LLMs, systematically examining the complete model life cycle from data curation to post-training through advanced prompting paradigms, code pre-training, supervised fine-tuning, reinforcement learning, and autonomous coding agents. |
JIAN YANG et. al. | arxiv-cs.SE | 2025-11-23 |
| 389 | PrefixGPT: Prefix Adder Optimization By A Generative Pre-trained Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce PrefixGPT, a generative pre-trained Transformer (GPT) that directly generates optimized prefix adders from scratch. |
Ruogu Ding; Xin Ning; Ulf Schlichtmann; Weikang Qian; | arxiv-cs.LG | 2025-11-22 |
| 390 | Enhancing Large Language Models for Automated Homework Assessment in Undergraduate Circuit Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This research full paper presents an enhancement pipeline for large language models (LLMs) in assessing homework for an undergraduate circuit analysis course, aiming to improve LLMs’ capacity to provide personalized support to electrical engineering students. |
LIANGLIANG CHEN et. al. | arxiv-cs.CY | 2025-11-22 |
| 391 | CATEGORY-BASED SENTIMENT ANALYSIS OF SINDHI NEWS HEADLINES USING MACHINE LEARNING DEEP LEARNING AND TRANSFORMER MODELS Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This work provides a foundational resource for NLP researchers seeking to advance computational methods for Sindhi and similar underrepresented languages. |
Dr. RAKESH; | International Journal of Data Science and IoT Management … | 2025-11-22 |
| 392 | A Cloud-Based Cross-Modal Transformer for Emotion Recognition and Adaptive Human-Computer Interaction Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, existing systems often rely on single-modality analysis such as facial expressions, speech tone, or textual sentiment, resulting in limited robustness and poor generalization in real-world environments. To address these challenges, this study proposes a Cloud-Based Cross-Modal Transformer (CMT) framework for multimodal emotion recognition and adaptive human-computer interaction. |
Ziwen Zhong; Zhitao Shu; Yue Zhao; | arxiv-cs.CV | 2025-11-21 |
| 393 | PARROT: Persuasion and Agreement Robustness Rating of Output Truth – A Sycophancy Robustness Benchmark for LLMs Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: This study presents PARROT (Persuasion and Agreement Robustness Rating of Output Truth), a robustness focused framework designed to measure the degradation in accuracy that occurs … |
Yusuf Çelebi; Özay Ezerceli; Mahmoud El Hussieni; | ArXiv | 2025-11-21 |
| 394 | A Scientometric Survey of BERT and Transformer-based Research: An Analysis of 200 Highly-cited Scopus Publications Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The study discloses a quick evolution from foundational architectural innovations and pre-training paradigms to widespread domain adaptation, rigorous model optimization for efficiency, and critical examination of model capabilities and societal effects. |
Ayman Mahgoub; | Scientometrica | 2025-11-21 |
| 395 | Deep Learning Approaches for Multi-Class Classification of Phishing Text Messages Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This research proposes a chain transformer model that integrates GPT-2 for synthetic data generation and BERT for embeddings to detect Smishing within a multiclass dataset, including minority smishing variants. |
Miriam L. Munoz; Muhammad F. Islam; | Journal of Cybersecurity and Privacy | 2025-11-21 |
| 396 | Swin‐Decision Transformer: A Transformer‐Based Hybrid Protocol for Adaptive Clustering and Energy‐Efficient Routing in Large‐Scale WSNs Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: In this era, large‐scale Wireless Sensor Networks (WSNs) provide high Quality of Service (QoS) with energy awareness and scalability. Specifically, existing clustering protocols … |
Basavaraj S. Mathapati; Nagaratna P. Hegde; S. P. Paramesh; Padmavathi Vurubindi; Subhra Chakraborty; | Internet Technology Letters | 2025-11-21 |
| 397 | NX-CGRA: A Programmable Hardware Accelerator for Core Transformer Algorithms on Edge Devices Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper introduces NX-CGRA, a programmable hardware accelerator designed to support a range of transformer inference algorithms, including both linear and non-linear functions. |
Rohit Prasad; | arxiv-cs.AR | 2025-11-21 |
| 398 | Pier: Efficient Large Language Model Pretraining with Relaxed Global Communication Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Global communication, such as all-reduce and allgather, is the prominent performance bottleneck in large language model (LLM) pretraining. To address this issue, we present Pier, an efficient and scalable optimizer with relaxed global communication. |
Shuyuan Fan; Zhao Zhang; | arxiv-cs.DC | 2025-11-21 |
| 399 | Enhancing Quranic Learning: A Multimodal Deep Learning Approach for Arabic Phoneme Recognition Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Accurate pronunciation detection remains a key challenge in Arabic, particularly in the context of Quranic recitation, where subtle phonetic differences can alter meaning. Addressing this challenge, the present study proposes a transformer-based multimodal framework for Arabic phoneme mispronunciation detection that combines acoustic and textual representations to achieve higher precision and robustness. |
Ayhan Kucukmanisa; Derya Gelmez; Sukru Selim Calik; Zeynep Hilal Kilimci; | arxiv-cs.SD | 2025-11-21 |
| 400 | Mining Emotions ‘A Comprehensive Study on Sentiment Analysis of Social Media’ Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study presents a comprehensive study of how SA techniques are applied to social media data to “mine emotions” effectively. |
Dr. Rupali Kalekar; Vyas More; Omkar Nalawade; | International Journal of Scientific Research in Engineering … | 2025-11-21 |
| 401 | Parrot: Persuasion and Agreement Robustness Rating of Output Truth — A Sycophancy Robustness Benchmark for LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study presents PARROT (Persuasion and Agreement Robustness Rating of Output Truth), a robustness focused framework designed to measure the degradation in accuracy that occurs under social pressure exerted on users through authority and persuasion in large language models (LLMs) the phenomenon of sycophancy (excessive conformity). |
Yusuf Çelebi; Mahmoud El Hussieni; Özay Ezerceli; | arxiv-cs.CL | 2025-11-21 |
| 402 | DSeq-JEPA: Discriminative Sequential Joint-Embedding Predictive Architecture Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Inspired by human visual perception, which deploys attention selectively and sequentially from the most informative to secondary regions, we propose DSeq-JEPA, a Discriminative Sequential Joint-Embedding Predictive Architecture that bridges predictive and autoregressive self-supervised learning, integrating JEPA-style latent prediction with GPT-style sequential reasoning. |
XIANGTENG HE et. al. | arxiv-cs.CV | 2025-11-21 |
| 403 | Leveraging Transformer-based Models for Classification and Large Language Models for Information Extraction from Medical Claims Documents Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The study explores the use of advanced AI models for document classification and information extraction in Indonesian medical claims documents. |
Dian Prambini; Kusworo Adi; Komang Budi Aryasa; | SISFORMA | 2025-11-21 |
| 404 | Multilingual Sentiment Analysis in E-commerce Customer Reviews Using GPT and Deep Learning-based Weighted-ensemble Model Related Papers Related Patents Related Grants Related Venues Related Experts View Save |
NUZHAT NOOR ISLAM PROVA et. al. | International Journal of Cognitive Computing in Engineering | 2025-11-20 |
| 405 | Evaluating Adversarial Vulnerabilities in Modern Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents a comparative analysis of the susceptibility to jailbreak attacks for two leading publicly available LLMs, Google’s Gemini 2.5 Flash and OpenAI’s GPT-4 (specifically the GPT-4o mini model accessible in the free tier). |
Tom Perel; | arxiv-cs.CR | 2025-11-20 |
| 406 | Can Open-Source Large Language Models Detect Medical Errors in Real-World Ophthalmology Reports? Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study prospectively compared contemporary large language models (LLMs) for detecting clinically salient errors in emergency ophthalmology encounter notes and generating actionable corrections. |
ANTE KRESO et. al. | AI | 2025-11-20 |
| 407 | Early Science Acceleration Experiments with GPT-5 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present a collection of short case studies in which GPT-5 produced new, concrete steps in ongoing research across mathematics, physics, astronomy, computer science, biology, and materials science. |
SÉBASTIEN BUBECK et. al. | arxiv-cs.CL | 2025-11-20 |
| 408 | BlockCert: Certified Blockwise Extraction of Transformer Mechanisms Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce BlockCert, a framework for certified blockwise extraction of transformer mechanisms, and outline how a lightweight extension can support certified local edits. |
Sandro Andric; | arxiv-cs.LG | 2025-11-20 |
| 409 | A Modular Architecture for Scalable Multilingual Natural Language Processing Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper proposes a novel, unified Modular Multilingual NLP (MM-NLP) architecture designed to streamline cross-lingual analysis through a cohesive, high- throughput workflow. |
Ravi Deo; Yash Bhadauria; Prof(Dr) V Sathyasuntharam; | International Scientific Journal of Engineering and … | 2025-11-19 |
| 410 | Evaluating The Effectiveness of Transformer-Based NLP Models in Maintaining Character Consistency (Personality and Tone) in Multi-Turn Game Dialogues Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper examines the progress of Transformer-based Natural Language Processing (NLP) models in NPC dialogue generation, with particular attention to studies that compare model selection such as GPT-2, DialoGPT, and GPT-Neo, approaches for sustaining consistency including fine-tuning, knowledge graphs, and rewriting, and evaluation using both automated metrics and human judgment. |
Qiyuan Zheng; | Applied and Computational Engineering | 2025-11-19 |
| 411 | Development of A Bariatric Surgery Specific Artificial Intelligence Large Language Model: BariatricSurgeryGPT Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The specialty-specific models could enhance surgical education through interactive learning tools, improve patient communication via personalized educational materials, and support clinical decision-making by providing evidence-based information synthesis. |
Berk B Ozmen; Ibrahim Berber; Jerry T Dang; Graham S Schwarz; Matthew Kroh; | Surgical Innovation | 2025-11-19 |
| 412 | Mosformer: Maliciously Secure Three-Party Inference Framework for Large Transformers Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Transformer-based models like BERT and GPT have achieved state-of-the-art performance across a wide range of AI tasks but raise serious privacy concerns when deployed as cloud … |
KE CHENG et. al. | Proceedings of the 2025 ACM SIGSAC Conference on Computer … | 2025-11-19 |
| 413 | Attention Via Synaptic Plasticity Is All You Need: A Biologically Inspired Spiking Neuromorphic Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Current spiking attention (i) relies on dot-product or element-wise similarity suited to floating-point operations, not event-driven spikes; (ii) keeps attention matrices that suffer from the von Neumann bottleneck, limiting in-memory computing; and (iii) still diverges from brain-like computation. To address these issues, we propose the Spiking STDP Transformer (S$^{2}$TDPT), a neuromorphic Transformer that implements self-attention through spike-timing-dependent plasticity (STDP), embedding query–key correlations in synaptic weights. |
Kallol Mondal; Ankush Kumar; | arxiv-cs.NE | 2025-11-18 |
| 414 | Financial Text Analysis and Credit Risk Assessment Using A GPT-4 and Improved BERT Fusion Model Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study aims to improve the identification of potential credit risks in unstructured financial texts. |
Huirong Tan; Yanruixue Xie; | PLOS One | 2025-11-18 |
| 415 | AdamHD: Decoupled Huber Decay Regularization for Language Model Pre-Training Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose AdamHuberDecay, a drop-in replacement for AdamW that substitutes the $\ell_2$ penalty with a decoupled smooth Huber regularizer. |
Fu-Ming Guo; Yingfang Fan; | arxiv-cs.LG | 2025-11-18 |
| 416 | Typology of Image Crises Using Large Language Models: A Novel Approach to Crisis Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Based on an analysis of 300 actual crisis cases, we propose an original typology that captures various types and causes of crises. |
GRZEGORZ CHODAK et. al. | Journal of Contingencies and Crisis Management | 2025-11-18 |
| 417 | Do Large Language Models (LLMs) Understand Chronology? Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Overall, our main contribution is showing that allocating explicit reasoning budget helps with chronological ordering with GPT-5 at medium/high reasoning effort achieving flawless ordering at all lengths and perfect conditional sorting (both self-filtered and given-subset), whereas low/minimal effort degrades with longer lists, mirroring earlier models. |
Pattaraphon Kenny Wongchamcharoen; Paul Glasserman; | arxiv-cs.AI | 2025-11-18 |
| 418 | UniSER: A Foundation Model for Unified Soft Effects Removal Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Leveraging the common essence of soft effects, i.e., semi-transparent occlusions, we introduce a foundational versatile model UniSER, capable of addressing diverse degradations caused by soft effects within a single framework. |
JINGDONG ZHANG et. al. | arxiv-cs.CV | 2025-11-18 |
| 419 | Bridging Human and Model Perspectives: A Comparative Analysis of Political Bias Detection in News Media Using Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study aims to present a comparative framework for evaluating the detection of political bias across human annotations and multiple LLMs, including GPT, BERT, RoBERTa, and FLAN. |
Shreya Adrita Banik; Niaz Nafi Rahman; Tahsina Moiukh; Farig Sadeque; | arxiv-cs.CL | 2025-11-18 |
| 420 | Demographic Biases in AI-generated Simulated Patient Cohorts: A Comparative Analysis Against Census Benchmarks Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Abstract Background Generative artificial intelligence models are being introduced as low-cost tools for creating simulated patient cohorts in undergraduate medical education. |
Miriam Veenhuizen; Andrew O’Malley; | Advances in Simulation | 2025-11-18 |
| 421 | Predictive Compliance Modeling Using Natural Language Processing for Real Time Regulatory Intelligence and Policy Deviation Detection in Hospitals Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This review examines the emerging field of predictive compliance modeling powered by natural language processing (NLP) for ensuring regulatory intelligence and policy deviation detection in hospitals. |
Getrude Frimpong; Amina Catherine Peter-Anyebe; Onuh Matthew Ijiga; | International Medical Science Research Journal | 2025-11-18 |
| 422 | Multimodal Generative Architectures for Knowledge Automation: Applications in Educational Engineering and Technical Communication Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Generative Artificial Intelligence (GAI) represents a disruptive evolution in intelligent systems, enabling the automated creation of multimodal content across text, image, audio, and structured data. This article explores GAI as a framework for knowledge automation, focusing on its integration into engineering education, scientific visualization, and technical communication. |
David Asael Gutiérrez-Hernández; Dulce Aurora Velázquez-Vázquez; | International Journal of Research and Innovation in Applied … | 2025-11-18 |
| 423 | RAG-Driven Data Quality Governance for Enterprise ERP Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present an end-to-end pipeline combining automated data cleaning with LLM-driven SQL query generation, deployed on a production system managing 240,000 employee records over six months. |
SEDAT BIN VEDAT et. al. | arxiv-cs.DB | 2025-11-18 |
| 424 | Drug Review Sentiment Analysis: Applying Transformer-Based Models for Enhanced Healthcare Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this research, the use of various machine learning and transformer-based approaches to analyze sentiments in drug reviews and gain meaningful insights from patient reviews or opinions is outlined. |
Abhishek Chaudhary; Sangita Pokhrel; Swathi Ganesan; Prashant Bikram Shah; Nalinda Somasiri; | Journal of Data Science and Intelligent Systems | 2025-11-18 |
| 425 | Transformer Injectivity & Geometric Robustness – Analytic Margins and Bi-Lipschitz Uniformity of Sequence-Level Hidden States Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Under real-analytic assumptions on decoder-only Transformers, recent work shows that the map from discrete prompts to last-token hidden states is generically injective on finite prompt sets. We refine this picture: for each layer $\ell$ we define a collision discriminant $Δ^\ell \subset Θ$ and injective stratum $U^\ell = Θ\setminus Δ^\ell$, and prove a dichotomy — either the model is nowhere injective on the set, or $U^\ell$ is open and dense and every $F^\ell_θ$ is injective. |
Mikael von Strauss; | arxiv-cs.LG | 2025-11-17 |
| 426 | Dynamic Template Selection for Output Token Generation Optimization: MLP-Based and Transformer Approaches Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present Dynamic Template Selection (DTS), which adaptively matches response templates to query complexity, achieving significant cost reductions without compromising response quality. |
Bharadwaj Yadavalli; | arxiv-cs.CL | 2025-11-17 |
| 427 | Requirement Specification Semantic Pruning: An NLP Approach for Redundancy Identification Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study proposes a semantic pruning framework that uses advanced NLP techniques, with a focus on transformer-based models like BERT, to find and eliminate superfluous requirements from SRS documents. |
Naimisha Soni; | International Journal for Research in Applied Science and … | 2025-11-17 |
| 428 | Interpretable Ransomware Detection Using Hybrid Large Language Models: A Comparative Analysis of BERT, RoBERTa, and DeBERTa Through LIME and SHAP Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study presents a comparative analysis of three Transformer-based Large Language Models (LLMs) (BERT, RoBERTa, and DeBERTa) for ransomware detection using two structured datasets: UGRansome and Process Memory (PM). |
Elodie Mutombo Ngoie; Mike Nkongolo Wa Nkongolo; Peace Azugo; Mahmut Tokmak; | arxiv-cs.CR | 2025-11-17 |
| 429 | Evaluating Large Language Models for Diacritic Restoration in Romanian Texts: A Comparative Study Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study evaluates the performance of several large language models (LLMs) in restoring diacritics in Romanian texts. |
Mihai Dan Nadas; Laura Diosan; | arxiv-cs.CL | 2025-11-17 |
| 430 | Based on Data Balancing and Model Improvement for Multi-Label Sentiment Classification Performance Enhancement Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Our data balancing strategy ensured an even distribution across 28 emotion categories. Based on this dataset, we developed an enhanced multi-label classification model that combines pre-trained FastText embeddings, convolutional layers for local feature extraction, bidirectional LSTM for contextual learning, and an attention mechanism to highlight sentiment-relevant words. |
Zijin Su; Huanzhu Lv; Yuren Niu; Yiming Liu; | arxiv-cs.CL | 2025-11-17 |
| 431 | Performance of Large Language Models in Medical Licensing Examinations: A Systematic Review and Meta-analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Purpose: This study systematically evaluates and compares the performance of large language models (LLMs) in answering medical licensing examination questions. |
HANIYEH NOURI et. al. | Journal of Educational Evaluation for Health Professions | 2025-11-17 |
| 432 | Evidence of Phase Transitions in Small Transformer-Based Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Prior work, such as that of Wei et al., demonstrated these phenomena under model and data scaling, with transitions revealed after applying a log scale to training compute. In this work, we ask three complementary questions: (1) Are phase transitions unique to large models, or can they also be observed in small transformer-based language models? |
Noah Hong; Tao Hong; | arxiv-cs.CL | 2025-11-16 |
| 433 | Reproducibility Report: Test-Time Training on Nearest Neighbors for Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Due to infrastructure limitations, we introduce a memory-efficient retrieval implementation that loads only required line offsets rather than entire files, reducing RAM requirements from over 128 GB per server to 32 GB. |
Boyang Zhou; Johan Lindqvist; Lindsey Li; | arxiv-cs.CL | 2025-11-16 |
| 434 | Classification of Hope in Textual Data Using Transformer-Based Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents a transformer-based approach for classifying hope expressions in text. |
Chukwuebuka Fortunate Ijezue; Tania-Amanda Fredrick Eneye; Maaz Amjad; | arxiv-cs.CL | 2025-11-16 |
| 435 | Understanding The Complexities of Responsibly Sharing NSFW Content Online Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Disturbingly, we also find linguistic cues linked to non-consensual content sharing. To help platforms moderate such behavior, we trained a RoBERTa-based classification model, which outperforms GPT-4 and traditional classifiers such as logistic regression and random forest in identifying non-consensual content sharing, demonstrating superior performance in this specific task. |
SHALINI JANGRA et. al. | arxiv-cs.SI | 2025-11-16 |
| 436 | RingX: Scalable Parallel Attention for Long-Context Learning on HPC Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The attention mechanism has become foundational for remarkable AI breakthroughs since the introduction of the Transformer, driving the demand for increasingly longer context to … |
Junqi Yin; M. Palash; M. Shankar; Feiyi Wang; | Proceedings of the International Conference for High … | 2025-11-15 |
| 437 | Explainable Transformer-Based Email Phishing Classification with Adversarial Robustness Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study presents a hybrid approach that uses DistilBERT, a smaller, faster, and lighter version of the BERT transformer model for email classification. |
Sajad U P; | arxiv-cs.CR | 2025-11-15 |
| 438 | Analysing Personal Attacks in U.S. Presidential Debates Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Advances in deep learning and transformer-based models, particularly BERT and large language models (LLMs) have created new opportunities for automated detection of harmful language. Motivated by these developments, we present a framework for analysing personal attacks in U.S. presidential debates. |
Ruban Goyal; Rohitash Chandra; Sonit Singh; | arxiv-cs.CL | 2025-11-14 |
| 439 | Context-Emotion Aware Therapeutic Dialogue Generation: A Multi-component Reinforcement Learning Approach to Language Models for Mental Health Support Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper investigated the application of supervised fine-tuning (SFT) and reinforcement learning (RL) techniques to enhance GPT-2’s capacity for therapeutic dialogue generation. |
Eric Hua Qing Zhang; Julia Ive; | arxiv-cs.CL | 2025-11-14 |
| 440 | LLM-Assisted Formalization Enables Deterministic Detection of Statutory Inconsistency in The Internal Revenue Code Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study introduces a hybrid neuro-symbolic framework that achieves deterministic detection of statutory inconsistency in complex law. |
Borchuluun Yadamsuren; Steven Keith Platt; Miguel Diaz; | arxiv-cs.AI | 2025-11-14 |
| 441 | Enhancing Sarcasm Detection on Social Media: A Comprehensive Study Using LLMs and BERT with Multi-headed Attention on SARC Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Sarcasm detection in natural language processing (NLP) remains a complex challenge, especially in social media, where contextual clues are often subtle. This study addresses this challenge by leveraging transformer-based models, including BERT, GPT-3, Claude-2, and Llama-2, for sarcasm detection on a large dataset from the Self-Annotated Reddit Corpus (SARC). |
Lihong Zhang; Muhammad Faseeh; Syed Shehryar Ali Naqvi; Liang Hu; Anwar Ghani; | PLOS One | 2025-11-14 |
| 442 | Deep Learning in Automated Essay Scoring for Islamic Education: A Systematic Review Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Automated Essay Scoring (AES) is a computer-based scoring system that uses appropriate features to automatically assess or give feedback to students, by combining the power of Artificial Intelligence and natural language processing (NLP) to provide convenience and benefits for evaluators. This study aims to analyze the most effective algorithmic models in evaluating the accuracy and reliability of the Automated Essay Scoring (AES) system, especially in the context of Islamic religious education assessment, as well as examine its advantages and disadvantages in supporting objective and efficient learning evaluation. |
Rokhmatul Khoiro Amin Putri; Kusaeri Kusaeri; Suparto Suparto; | Online Learning In Educational Research (OLER) | 2025-11-14 |
| 443 | Multi-Phase Spacecraft Trajectory Optimization Via Transformer-Based Reinforcement Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This work introduces a transformer-based RL framework that unifies multi-phase trajectory optimization through a single policy architecture, leveraging the transformer’s inherent capacity to model extended temporal contexts. |
Amit Jain; Victor Rodriguez-Fernandez; Richard Linares; | arxiv-cs.LG | 2025-11-14 |
| 444 | Breaking CAPTCHA Using Transformer-Based OCR Models: A Deep Learning Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this research, we propose a novel approach using Optical Character Recognition (OCR) models based on Convolutional Recurrent Neural Networks (CRNN) and hybrid CNN-Transformer architectures to evaluate their efficacy in breaking CAPTCHA images. |
Abhinav Chaturvedi; | International Journal for Research in Applied Science and … | 2025-11-14 |
| 445 | Patients Prefer Human Empathy, But Not Always Human Wording: A Single-Blind Within-Subject Trial of GPT-Generated Vs. Clinician Discharge Texts in Emergency Ophthalmology Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Methods: We conducted a prospective, single-blind, within-subject study in the Emergency Ophthalmology Unit of the University Hospital Centre Split, Croatia. |
DEA SAMARDZIC et. al. | Clinics and Practice | 2025-11-14 |
| 446 | Transformers Vs. Recurrent Models for Estimating Forest Gross Primary Production Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Feature importance analysis reveals radiation as the dominant predictor, followed by Sentinel-2, MODIS land surface temperature, and Sentinel-1 contributions. Our results demonstrate how model architecture, context length, and multimodal inputs jointly determine performance in GPP prediction, guiding future developments of DL frameworks for monitoring terrestrial carbon dynamics. |
DAVID MONTERO et. al. | arxiv-cs.LG | 2025-11-14 |
| 447 | Identifying Imaging Follow-Up in Radiology Reports: A Comparative Analysis of Traditional ML and LLM Approaches Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we introduce an annotated corpus of 6,393 radiology reports from 586 patients, each labeled for follow-up imaging status, to support the development and benchmarking of follow-up adherence detection systems. |
NAMU PARK et. al. | arxiv-cs.CL | 2025-11-14 |
| 448 | Using Large Language Models As A Scalable Mental Status Evaluation Technique Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Given the usage of spoken language in diagnostics and treatment, it stands out as a potential methodology. With a substantial mismatch between the demand for services and the availability of care, this study focuses on leveraging large language models to bridge this gap. |
MARGOT WAGNER et. al. | NPP—Digital Psychiatry and Neuroscience | 2025-11-13 |
| 449 | Analogical Structure, Minimal Contextual Cues and Contrastive Distractors: Input Design for Sample-Efficient Linguistic Rule Induction Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We develop a computational approach implementing three cognitive-inspired principles: analogical structure, contrastive learning, and minimal contextual cues. |
Chunyang Jiang; Paola Merlo; | arxiv-cs.CL | 2025-11-13 |
| 450 | On The Military Applications of Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, military use cases or applications and implementation thereof are considered for natural language processing and large language models, which have broken into fame with the invention of the generative pre-trained transformer (GPT) and the extensive foundation model pretraining done by OpenAI for ChatGPT and others. |
Satu Johansson; Taneli Riihonen; | arxiv-cs.CL | 2025-11-13 |
| 451 | EXplainable AI Framework for Automated Lesson Plan Generation and Alignment with Bloom’s Taxonomy Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents an Explainable Artificial Intelligence (XAI) framework for the automated generation of lesson plans aligned with Bloom’s Taxonomy. |
Deborah Olaniyan; Julius Olaniyan; Ibidun C. Obagbuwa; Anthony K. Tsetse; | Computers | 2025-11-13 |
| 452 | Document Encoding Effects on Large Language Model Response Time and Consistency Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Large language models (LLMs) such as GPT-4 are increasingly integrated into research, industry, and enterprise workflows, yet little is known about how input file formats shape their outputs. |
Dianeliz Ortiz Martes; Nezamoddin N. Kachouie; | Computers | 2025-11-13 |
| 453 | Utility of Large Language Models for Congenital Microtia Reconstruction Education: Comparison of The Performance of Claude, GPT, and Gemini Related Papers Related Patents Related Grants Related Venues Related Experts View Save |
ZHIFENG LIAO et. al. | Aesthetic Plastic Surgery | 2025-11-13 |
| 454 | Automated Analysis of Learning Outcomes and Exam Questions Based on Bloom’s Taxonomy Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper explores the automatic classification of exam questions and learning outcomes according to Bloom’s Taxonomy. |
Ramya Kumar; Dhruv Gulwani; Sonit Singh; | arxiv-cs.CL | 2025-11-13 |
| 455 | Performance of Foundation Models Vs Physicians in Textual and Multimodal Ophthalmological Questions Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Objective To evaluate the multimodal performance of the following 7 foundation models (FMs): GPT-4o (OpenAI), Gemini 1.5 Pro (Google), Claude 3.5 Sonnet (Anthropic), Llama-3.2-11B (Meta), DeepSeek V3 (High-Flyer), Qwen2.5-Max (Alibaba Cloud), and Qwen2.5-VL-72B (Alibaba Cloud) in answering offline Fellowship of the Royal College of Ophthalmologists part 2 written multiple-choice textual and multimodal questions, with head-to-head comparisons with physicians. Design, Setting, and Participants This cross-sectional study was conducted between September 2024 and March 2025 using questions sourced from a textbook used as an examination preparation resource for the Fellowship of the Royal College of Ophthalmologists part 2 written examination. |
HENRY ROCHA et. al. | JAMA Ophthalmology | 2025-11-13 |
| 456 | Effects of Education Level on Natural Language Processing in Cardiovascular Health Communication Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study evaluated how natural language processing (NLP) models respond to CVD-related questions across different education levels. |
STANLEY JOSEPH et. al. | Frontiers in Public Health | 2025-11-13 |
| 457 | Improving Story Points Estimation Using Ensemble Machine Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study introduces an innovative ML-based ensemble stacking technique, combining RoBERTa, a transformer model for natural language processing, with BiLSTM, a neural network adept at handling sequential data. |
Zuhaimi Ahmad; Matthew M. Y. Kuo; | Software Quality Journal | 2025-11-13 |
| 458 | EMSA: Explainable Multilingual Sentiment Analysis Models Providing Sentiment Analysis Across Multiple Languages Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Sentiment analysis across multiple languages remains a challenging problem due to linguistic diversity, domain-specific expressions, and the limited explainability of existing models. This study aims to address these issues by proposing the Explainable Multilingual Sentiment Analyzer (EMSA), a novel framework that integrates large language models with prompt engineering. |
Li Zhao; Jinwei Zhou; Jinde Cao; Weina Zhu; | PLOS One | 2025-11-12 |
| 459 | Empowering GPT As A Processual Writer: Didactext-guided Prompting Improves Knowledge Access, Iterative Revision, and Overall Textual Quality Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This article investigates how guided prompting based on the Didactext model empowers GPT-4 to function as a processual writer, enhancing literacy processes in educational contexts. |
M. Teresa Mateo-Girona; Steffanie Kloss; Fernando Lillo-Fuentes; | Frontiers in Education | 2025-11-12 |
| 460 | Measuring Political Bias in LLMs Using Fine-Tuned RoBERTa Model Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Therefore, both the public and researchers are increasingly becoming concerned with the implicit political bias in these models’ outputs. This concern has prompted the present study to use a fine-tuned RoBERTa-base model in a supervised learning setting, with the goal of detecting political bias in any given text. |
Kondreddy karthik reddy; Vishnu Prasath K; Dr. Madhumitha. K; | INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING … | 2025-11-12 |
| 461 | An AI-driven Framework for Continuous Tourist Sentiment Scoring Using Longitudinal and Group-level Insights with Pre-trained Language Models (RoBERTa-CSS) Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Design/methodology/approach This paper proposed a tool named RoBERTa-CSS (RoBERTa-based Continuous Sentiment Scoring) to calculate tourists’ continuous sentiment scores based on the pre-trained language model RoBERTa. |
Tong Yang; Cathy H.C. Hsu; | Tourism Review | 2025-11-12 |
| 462 | Convergence Dynamics of Agent-to-Agent Interactions with Misaligned Objectives Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Our framework presents a setup to study, predict, and defend multi-agent systems; explicitly linking prompt design and interaction setup to stability, bias, and robustness. |
Romain Cosentino; Sarath Shekkizhar; Adam Earle; | arxiv-cs.MA | 2025-11-11 |
| 463 | Cost–benefit Analysis of Deploying Shallow, Deep Learning and Generative Models for Legal Text Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce the new CUAD-SL dataset that has been refactored as a single label classification problem as a fairer and more robust legal classification benchmark. |
EOIN O’CONNELL et. al. | Artificial Intelligence and Law | 2025-11-11 |
| 464 | VideoChain: A Transformer-Based Framework for Multi-hop Video Question Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Multi-hop Question Generation (QG) effectively evaluates reasoning but remains confined to text; Video Question Generation (VideoQG) is limited to zero-hop questions over single segments. To address this, we introduce VideoChain, a novel Multi-hop Video Question Generation (MVQG) framework designed to generate questions that require reasoning across multiple, temporally separated video segments. |
Arpan Phukan; Anupam Pandey; Deepjyoti Bodo; Asif Ekbal; | arxiv-cs.CV | 2025-11-11 |
| 465 | Decomposition of Small Transformer Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we extend Stochastic Parameter Decomposition (SPD) to Transformer models, proposing an updated causal importance function suited for sequential data and a new loss function. |
Casper L. Christensen; Logan Riggs; | arxiv-cs.LG | 2025-11-11 |
| 466 | EMAformer: Enhancing Transformer Through Embedding Armor for Time Series Forecasting Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We attribute this performance gap to unstable inter-channel relationships. To bridge this gap, we propose EMAformer, a simple yet effective model that enhances the Transformer with an auxiliary embedding suite, akin to armor that reinforces its ability. |
Zhiwei Zhang; Xinyi Du; Xuanchi Guo; Weihao Wang; Wenjuan Han; | arxiv-cs.LG | 2025-11-11 |
| 467 | Encoder Fine-tuning with Stochastic Sampling Outperforms Open-weight GPT in Astronomy Knowledge Extraction Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we present an encoder-based system for extracting knowledge from astronomy articles. |
Shivam Rawat; Lucie Flek; Akbar Karimi; | arxiv-cs.CL | 2025-11-11 |
| 468 | Can Large Language Models Simulate Symbolic Execution Output Like KLEE? Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this project, we wanted to see if a large language model like GPT-4o could simulate the kinds of outputs that KLEE generates. |
Rong Feng; Vanisha Gupta; Vivek Patel; Viroopaksh Reddy Ernampati; Suman Saha; | arxiv-cs.SE | 2025-11-11 |
| 469 | CellARC: Measuring Intelligence with Cellular Automata Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce CellARC, a synthetic benchmark for abstraction and reasoning built from multicolor 1D cellular automata (CA). |
Miroslav Lžičař; | arxiv-cs.LG | 2025-11-11 |
| 470 | Benchmarking Educational LLMs with Analytics: A Case Study on Gender Bias in Feedback Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This article presents an embedding-based benchmarking framework to detect bias in LLMs in the context of formative feedback. |
Yishan Du; Conrad Borchers; Mutlu Cukurova; | arxiv-cs.CL | 2025-11-11 |
| 471 | Efficient Transfer Learning for NLP: An Experimental Analysis of Dimensionality Reduction Techniques Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, an experimental comparison of DR methods like Latent Semantic Analysis (LSA), Chi-Square feature selection, and Principal Component Analysis (PCA), in transfer learning for sentiment classification. |
Mrs. Vaishali Suryawanshi; Dr. Abhijeet Kaiwade; | International Journal of Research and Innovation in Applied … | 2025-11-10 |
| 472 | Jailbreaking LLMs Through Cross-Cultural Prompts Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We examine how linguistic and cultural framing affect jailbreak success in three commercial LLMs (GPT-4, Claude 3, Gemini), using semantically equivalent prompts in direct, indirect, and metaphorical styles across four high-resource languages. |
Damin Kim; Minseok Hur; Jeongin Lee; Moohong Min; | cikm | 2025-11-10 |
| 473 | Biologically-Informed Hybrid Membership Inference Attacks on Generative Genomic Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This work explores the use of language models (LMs) for the generation of synthetic genetic mutation profiles, leveraging differential privacy (DP) for the protection of sensitive genetic data. |
Asia Belfiore; Jonathan Passerat-Palmbach; Dmitrii Usynin; | arxiv-cs.CR | 2025-11-10 |
| 474 | SST: Multi-Scale Hybrid Mamba-Transformer Experts for Time Series Forecasting Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Then we show that Mamba excels at capturing long-term structures, while Transformer is more effective at modeling short-term dynamics. Building on this insight, we propose State Space Transformer (SST), a multi-scale hybrid model with expert modules: a Mamba expert for long-range patterns and a Transformer expert for short-term variations. |
XIONGXIAO XU et. al. | cikm | 2025-11-10 |
| 475 | Evaluating LLMs for Anxiety, Depression, and Stress Detection Evaluating Large Language Models for Anxiety, Depression, and Stress Detection: Insights Into Prompting Strategies and Synthetic Data Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Overall, this workemphasizes the potential of combining advanced language models and dataaugmentation to enhance automated mental health assessment from text. |
Mihael Arcan; David-Paul Niland; | arxiv-cs.CL | 2025-11-10 |
| 476 | SCALAR: Benchmarking SAE Interaction Sparsity in Toy LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce SCALAR (Sparse Connectivity Assessment of Latent Activation Relationships), a benchmark measuring interaction sparsity between SAE features. |
SEAN P. FILLINGHAM et. al. | arxiv-cs.LG | 2025-11-10 |
| 477 | Applied Theory of Mind and Large Language Models – How Good Is ChatGPT at Solving Social Vignettes? Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Parents of autistic persons emphasize the importance of appropriate and context-specific communication behavior. This study investigated whether GPT-3.5 Turbo and GPT-4, as language-based AI applications, are fundamentally capable of replicating this type of adequate communication behavior in the form of applied Theory of Mind (ToM). |
ANNA KATHARINA HOLL-ETTEN et. al. | arxiv-cs.HC | 2025-11-10 |
| 478 | Evaluating Large Language Models in Interpreting MRI Reports and Recommending Treatment for Vestibular Schwannoma Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To evaluate and compare the diagnostic accuracy and treatment recommendations provided by GPT-4, Gemini, and Bing for patients with VS based on MRI reports, while addressing the growing use of these tools by patients seeking medical information. Methods: This retrospective study included 35 consecutive patients with VS treated at a university-based neurosurgery department. |
Arthur H. A. Sales; Christine Julia Gizaw; Jürgen Beck; Jürgen Grauvogel; | Diagnostics | 2025-11-10 |
| 479 | Automated Detection of Stigmatizing Language in Electronic Health Records (EHRs) Using A Multi-stage Transfer Learning Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Abstract Objective Stigmatizing language (SL) in Electronic Health Records (EHRs) can perpetuate biases and negatively impact patient care. This study introduces a novel method for automatically detecting such language to improve healthcare documentation practices. |
Liyang Xue; A M Muntasir Rahman; Charles R Senteio; Vivek K Singh; | Journal of the American Medical Informatics Association | 2025-11-09 |
| 480 | Comparing Reconstruction Attacks on Pretrained Versus Full Fine-tuned Large Language Model Embeddings on Homo Sapiens Splice Sites Genomic Data Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Building upon Pan et al.’s seminal work demonstrating that embeddings from pretrained language models can leak sensitive information, we conduct a comprehensive analysis using the HS3D genomic dataset to determine whether task-specific optimization strengthens or weakens privacy protections. |
Reem Al-Saidi; Erman Ayday; Ziad Kobti; | arxiv-cs.LG | 2025-11-09 |
| 481 | Enhancing Conversational Agent Responses with EXLNetT Using Learnable Enhanced Laplacian Kernel Attention Mechanism, Deep Bi-affine Network, and Hybrid Positional Encoding Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: In natural language computing, AI-based Conversational Agents are pivotal in enhancing human-computer interaction. Although transformer models like XLNet and GPT-3 have shown … |
N Muthukumaran; A Vignesh; | The Computer Journal | 2025-11-09 |
| 482 | EcoSpa: Efficient Transformer Training with Coupled Sparsity Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce EcoSpa, an efficient structured sparse training method that jointly evaluates and sparsifies coupled weight matrix pairs, preserving their interaction patterns through aligned row/column removal. |
JINQI XIAO et. al. | arxiv-cs.LG | 2025-11-09 |
| 483 | Large Language Models Can Identify The Presence of MASH and Extract VCTE Measurements from Unstructured Documentation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Methods We used a cohort of 493 patients with compensated MASH cirrhosis. |
ARYANA T. FAR et. al. | Digestive Diseases and Sciences | 2025-11-08 |
| 484 | Psychological Stress During Examination and Its Estimation By Handwriting in Answer Script Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: By leveraging Optical Character Recognition and transformer based sentiment analysis models, we present a data driven approach that transcends traditional grading systems, offering deeper insights into cognitive and emotional states during examinations. |
Abhijeet Kumar; Chetan Agarwal; Pronoy B. Neogi; Mayank Goswami; | arxiv-cs.CV | 2025-11-08 |
| 485 | Understanding Social Media Mood During Global Events: A Sentiment and Topic Modeling Study of FIFA 2022 Tweets Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this study, we trained multiple NLP models—including LSTM, BERT, RoBERTa, and DistilBERT—selected to represent both deep learning baselines and state-of-the-art transformer-based architectures, in order to ensure a balanced and comparative evaluation. |
Vishal Mehra; Sandeep Sood; Prabhsimran Singh; | Engineering Research Express | 2025-11-07 |
| 486 | Whose Instructions Count? Resolving Preference Bias in Instruction Fine-Tuning Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose Dynamic Cross-Layer Preference Correction (\textsc{DCPC}), it couples (i) a preference-sensitive similarity estimator that detects mismatched instructional cues, (ii) cross-layer prefix alignment to reconcile semantic representations across transformer layers, and (iii) a lightweight Preference Correction Module (PCM) that dynamically adjusts hidden states to honor the inferred dominant preference. |
JIAYU ZHANG et. al. | nips | 2025-11-07 |
| 487 | Exploring Diffusion Transformer Designs Via Grafting Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: To this end, we present *grafting*, a simple approach for editing pretrained diffusion transformers (DiTs) to materialize new architectures under small compute budgets. |
KESHIGEYAN CHANDRASEGARAN et. al. | nips | 2025-11-07 |
| 488 | LLM Strategic Reasoning: Agentic Study Through Behavioral Game Theory Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Yet, most evaluations of large language models (LLMs) for strategic decision-making often rely heavily on Nash Equilibrium (NE) benchmarks, overlook reasoning depth, and fail to reveal the mechanisms behind model behavior. To address this gap, we introduce a behavioral game-theoretic evaluation framework that disentangles intrinsic reasoning from contextual influence. |
Jingru Jia; Zehua Yuan; Junhao Pan; Paul E McNamara; Deming Chen; | nips | 2025-11-07 |
| 489 | OmniConsistency: Learning Style-Agnostic Consistency from Paired Stylization Data IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: GPT-4o’s exceptional stylization consistency highlights the performance gap between open-source methods and proprietary models. To bridge this gap, we propose \textbf{OmniConsistency}, a universal consistency plugin leveraging large-scale Diffusion Transformers (DiTs). |
Yiren Song; Cheng Liu; Mike Zheng Shou; | nips | 2025-11-07 |
| 490 | Efficient Classification of Human-Generated Vs. Machine-Generated Text Using Lightweight Machine Learning Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study presents an efficient and interpretable approach to distinguishing human-authored text from machine-generated content using traditional machine learning techniques, thereby avoiding the computational demands of transformer-based classifiers. |
Kian Jazayeri; | International Journal on Artificial Intelligence Tools | 2025-11-07 |
| 491 | Improving Formal Reasoning of Transformer with State Stack Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Drawing inspiration from pushdown automata, which efficiently resolve deterministic context-free grammars using stacks, we equip layers with a differentiable stack and propose StackTrans to address the aforementioned issue within LLMs. |
KECHI ZHANG et. al. | nips | 2025-11-07 |
| 492 | DeltaFormer: Unlock The State Space of Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To this end, we have re-examined the Transformer from the perspective of a state space with kernel functions and propose an improved Transformer called DeltaFormer. |
MINGYU XU et. al. | nips | 2025-11-07 |
| 493 | TPP-SD: Accelerating Transformer Point Process Sampling with Speculative Decoding Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose TPP-SD, a novel approach that accelerates Transformer temporal point process (TPP) sampling by adapting speculative decoding (SD) techniques from language models. |
Shukai Gong; YIYANG FU; Fengyuan Ran; Quyu Kong; Feng Zhou; | nips | 2025-11-07 |
| 494 | Large Language Diffusion Models IF:6 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The capabilities of large language models (LLMs) are widely regarded as relying on autoregressive models (ARMs). We challenge this notion by introducing *LLaDA*, a diffusion model trained from scratch under the pre-training and supervised fine-tuning (SFT) paradigm. |
SHEN NIE et. al. | nips | 2025-11-07 |
| 495 | Learning in Compact Spaces with Approximately Normalized Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we propose a more holistic, approximate normalization via simple scalar multiplications motivated by the tight concentration of the norms of high-dimensional random vectors. |
JÖRG K.H. FRANKE et. al. | nips | 2025-11-07 |
| 496 | Feature Fusion Based Transformer for Sentiment Analysis in Social Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Sentiment analysis methods aim to evaluate users’ mental health conditions by analyzing their posted content (text, images, and audio) on social networks. |
Shiyong Li; He Li; Juan Du; Shitao Yan; Chuang Dong; | PLOS One | 2025-11-07 |
| 497 | SketchMind: A Multi-Agent Cognitive Framework for Assessing Student-Drawn Scientific Sketches Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Existing solutions often treat sketch evaluation as either an image classification task or monolithic vision-language models, which lack interpretability, pedagogical alignment, and adaptability across cognitive levels. To address these limitations, we present SketchMind, a cognitively grounded, multi-agent framework for evaluating and improving student-drawn scientific sketches. |
Ehsan Latif; Zirak Khan; Xiaoming Zhai; | nips | 2025-11-07 |
| 498 | Lost in Transmission: When and Why LLMs Fail to Reason Globally Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We argue that these failures arise due to capacity limits on the accurate flow of information within LLMs. To formalize this issue, we introduce the bounded attention prefix oracle (BAPO) model, a new computational framework that models bandwidth constraints on attention heads, the mechanism for internal communication in LLMs. |
Tobias Schnabel; Kiran Tomlinson; Adith Swaminathan; Jennifer Neville; | nips | 2025-11-07 |
| 499 | Video-RAG: Visually-aligned Retrieval-Augmented Long Video Comprehension IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: In this paper, we propose Video Retrieval-Augmented Generation (Video-RAG), a training-free and cost-effective pipeline that employs visually-aligned auxiliary texts to help facilitate cross-modality alignment while providing additional information beyond the visual content. |
YONGDONG LUO et. al. | nips | 2025-11-07 |
| 500 | From Noise to Narrative: Tracing The Origins of Hallucinations in Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In the present work, we establish how and when hallucinations arise in pre-trained transformer models through concept representations captured by sparse autoencoders, under scenarios with experimentally controlled uncertainty in the input space. |
Praneet Suresh; Jack Stanley; Sonia Joseph; Luca Scimeca; Danilo Bzdok; | nips | 2025-11-07 |
| 501 | Teaching Transformers to Solve Combinatorial Problems Through Efficient Trial & Error Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Despite their proficiency in various language tasks, Large Language Models (LLMs) struggle with combinatorial problems like Satisfiability, Traveling Salesman Problem, or even basic arithmetic. We address this gap through a novel approach for solving problems in the class NP. |
Panagiotis Giannoulis; Yorgos Pantis; Christos Tzamos; | nips | 2025-11-07 |
| 502 | VL-Rethinker: Incentivizing Self-Reflection of Vision-Language Models with Reinforcement Learning IF:4 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: In this paper, we aim to enhance the slow-thinking capabilities of vision-language models using reinforcement learning (without relying on distillation) to advance the state of the art. |
HAOZHE WANG et. al. | nips | 2025-11-07 |
| 503 | EfficientNav: Towards On-Device Object-Goal Navigation with Navigation Map Caching and Retrieval Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we propose EfficientNav to enable on-device efficient LLM-based zero-shot ObjNav. |
ZEBIN YANG et. al. | nips | 2025-11-07 |
| 504 | EAP-GP: Mitigating Saturation Effect in Gradient-based Automated Circuit Identification Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we revisit existing gradient-based circuit identification methods and find that their performance is either affected by the zero-gradient problem or saturation effects, where edge attribution scores become insensitive to input changes, resulting in noisy and unreliable attribution evaluations for circuit components. |
LIN ZHANG et. al. | nips | 2025-11-07 |
| 505 | Dual-Comb Ghost Imaging with Transformer-Based Reconstruction for Optical Fiber Endomicroscopy Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Optical fibers offer a sub-millimeter-scale imaging conduit that could meet this need, but existing fiber-based approaches typically require either raster scanning or multicore bundles, which limit resolution and speed of imaging. In this work, we overcome these limitations by combining dual-comb interferometry with optical ghost imaging and advanced algorithm. |
DAVID DANG et. al. | nips | 2025-11-07 |
| 506 | A Frustratingly Simple Yet Highly Effective Attack Baseline: Over 90% Success Rate Against The Strong Black-box Models of GPT-4.5/4o/o1 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: This critical absence of semantic information leads commercial black-box LVLMs to either ignore the perturbation entirely or misinterpret its embedded semantics, thereby causing the attack to fail. To overcome these issues, we propose to refine semantic clarity by encoding explicit semantic details within local regions, thus ensuring the capture of finer-grained features and inter-model transferability, and by concentrating modifications on semantically rich areas rather than applying them uniformly. |
Zhaoyi Li; Xiaohan Zhao; Dong-Dong Wu; Jiacheng Cui; Zhiqiang Shen; | nips | 2025-11-07 |
| 507 | Optimal Control for Transformer Architectures: Enhancing Generalization, Robustness and Efficiency Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We conduct seven extensive experiments on tasks motivated by text generation, sentiment analysis, image classification, and point cloud classification. |
KELVIN KAN et. al. | nips | 2025-11-07 |
| 508 | Causal Discovery and Inference Through Next-Token Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Here we demonstrate that a GPT-style transformer trained for next-token prediction can simultaneously discover instances of linear Gaussian structural causal models (SCMs) and learn to answer counterfactual queries about those SCMs. |
Eivinas Butkus; Nikolaus Kriegeskorte; | nips | 2025-11-07 |
| 509 | Memory Mosaics at Scale Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To this end, we scale memory mosaics to 10B size, we train them on one trillion tokens, we introduce a couple architectural modifications (*memory mosaics v2*), we assess their capabilities across three evaluation dimensions: training-knowledge storage, new-knowledge storage, and in-context learning. |
Jianyu Zhang; Leon Bottou; | nips | 2025-11-07 |
| 510 | StarTrail: Concentric Ring Sequence Parallelism for Efficient Near-Infinite-Context Transformer Model Training Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Current methods are either constrained by the number of attention heads or excessive communication overheads. To address this problem, we propose StarTrail, a multi-dimensional concentric distributed training system for long sequences, fostering an efficient communication paradigm and providing additional tuning flexibility for communication arrangements. |
ZIMING LIU et. al. | nips | 2025-11-07 |
| 511 | Web-Shepherd: Advancing PRMs for Reinforcing Web Agents Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: Despite the importance of speed and cost-effectiveness, prior works have utilized MLLMs as reward models, which poses significant constraints for real-world deployment. To address this, in this work, we propose the first process reward model (PRM) called Web-Shepherd which could assess web navigation trajectories in a step-level. |
HYUNGJOO CHAE et. al. | nips | 2025-11-07 |
| 512 | Large Language Models Think Too Fast To Explore Effectively Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: This study investigates whether LLMs can surpass humans in exploration during an open-ended task, using Little Alchemy 2 as a paradigm, where agents combine elements to discover new ones. |
Lan Pan; Hanbo Xie; Robert Wilson; | nips | 2025-11-07 |
| 513 | Wavy Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we establish an equivalence between the hidden-state dynamics induced by stacked attention layers and graph neural diffusion on a complete graph. |
Satoshi Noguchi; Yoshinobu Kawahara; | nips | 2025-11-07 |
| 514 | First Attentions Last: Better Exploiting First Attentions for Efficient Parallel Training Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Motivated by the observations, we propose FAL (First Attentions Last), an efficient transformer architecture that redirects the first MHA output to the MLP inputs of the following layers, eliminating the per-block MHA-MLP connections. |
GYUDONG KIM et. al. | nips | 2025-11-07 |
| 515 | Explainable Detection: A Transformer-based Language Modeling Approach for Bengali News Title Classification with Comparative Explainability Analysis Using ML and DL Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study underscores the potential of deep learning models in advancing text classification for the Bengali language and emphasizes the critical role of explainability in AI-driven solutions. |
Md. Julkar Naeen; Sourav Kumar Das; Sakib Alam Jisan; Sharun Akter Khushbu; Noyon Chandra Saha; | Frontiers in Artificial Intelligence | 2025-11-06 |
| 516 | Post-Training LLMs As Better Decision-Making Agents: A Regret-Minimization Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Yet, since theywere not originally designed for DM, recent studies show that LLMs can struggleeven in basic online DM problems, failing to achieve low regret or an effectiveexploration-exploitation tradeoff. To address this, we introduce IterativeRegret-Minimization Fine-Tuning (Iterative RMFT), a post-training procedurethat repeatedly distills low-regret decision trajectories back into the basemodel. |
Chanwoo Park; Ziyang Chen; Asuman Ozdaglar; Kaiqing Zhang; | arxiv-cs.AI | 2025-11-06 |
| 517 | Implementation of Transformer-based LLMs with Large-scale Optoelectronic Neurons on A CMOS Image Sensor Platform Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we propose andanalyze the implementation of the transformer model, which is the cornerstoneof the modern LLMs, with novel large-scale optoelectronic neurons (OENs)constructed over the commercially available complementarymetal-oxide-semiconductor (CMOS) image sensor (CIS) platform. |
NEIL NA et. al. | arxiv-cs.ET | 2025-11-06 |
| 518 | LLMCARE: Early Detection of Cognitive Impairment Via Transformer Models Enhanced By LLM-generated Synthetic Data Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Speech-based natural language processing (NLP) provides a scalable approach to identify early cognitive decline by detecting subtle linguistic markers that may precede clinical diagnosis. |
ALI ZOLNOUR et. al. | Frontiers in Artificial Intelligence | 2025-11-06 |
| 519 | GPT-5 at CTFs: Case Studies From Top-Tier Cybersecurity Events Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We show frontier AI is similarly good at hacking byletting GPT-5 compete in elite CTF cybersecurity competitions. |
Artem Petrov; Dmitrii Volkov; | arxiv-cs.CR | 2025-11-06 |
| 520 | Evaluating AI Models for Autograding Explain in Plain English Questions: Challenges and Considerations Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: One way to assess code reading ability is using Explain in Plain English (EiPE) questions, which ask students to describe what a piece of code does with natural language. |
MAX FOWLER et. al. | ACM Transactions on Interactive Intelligent Systems | 2025-11-06 |
| 521 | Trustworthiness Calibration Framework for Phishing Email Detection Using Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: While large language models (LLMs)such as GPT-4 and LLaMA-3-8B achieve strong accuracy in text classification,their deployment in security systems requires assessing reliability beyondbenchmark performance. To address this, this study introduces theTrustworthiness Calibration Framework (TCF), a reproducible methodology forevaluating phishing detectors across three dimensions: calibration,consistency, and robustness. |
Daniyal Ganiuly; Assel Smaiyl; | arxiv-cs.CR | 2025-11-06 |
| 522 | Exploring The Psychometric Validity of AI-Generated Student Responses: A Study on Virtual Personas’ Learning Motivation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study explores whether large language models (LLMs) can simulate valid student responses for educational measurement. |
Huanxiao Wang; | arxiv-cs.CY | 2025-11-05 |
| 523 | Comparing The Performance of LLMs in RAG-based Question-Answering: A Case Study in Computer Science Literature Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Evaluationmetrics employed in the study include accuracy and precision for binaryquestions and ranking by a human expert, ranking by Google’s AI model Gemini,alongside cosine similarity for long-answer questions. |
Ranul Dayarathne; Uvini Ranaweera; Upeksha Ganegoda; | arxiv-cs.CL | 2025-11-05 |
| 524 | From GPT to LLaMA: Tracing The Growth of Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We examine key breakthroughs in scaling (e.g., the GPT series, PaLM, LLaMA), highlighting how increasing model size has led to emergent capabilities in language understanding and generation. |
Jiarui Gu; | Theoretical and Natural Science | 2025-11-05 |
| 525 | How Different Tokenization Algorithms Impact LLMs and Transformer Models for Binary Code Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Despite its significance, tokenization in thecontext of assembly code remains an underexplored area. This study aims toaddress this gap by evaluating the intrinsic properties of Natural LanguageProcessing (NLP) tokenization models and parameter choices, such as vocabularysize. |
Ahmed Mostafa; Raisul Arefin Nahid; Samuel Mulder; | arxiv-cs.AI | 2025-11-05 |
| 526 | Evaluating Modern Large Language Models on Low-Resource and Morphologically Rich Languages:A Cross-Lingual Benchmark Across Cantonese, Japanese, and Turkish Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we present a comprehensive evaluation of seven cutting-edge LLMs — including GPT-4o, GPT-4, Claude~3.5~Sonnet, LLaMA~3.1, Mistral~Large~2, LLaMA-2~Chat~13B, and Mistral~7B~Instruct — on a new cross-lingual benchmark covering \textbf{Cantonese, Japanese, and Turkish}. |
CHENGXUAN XIA et. al. | arxiv-cs.CL | 2025-11-05 |
| 527 | Do Artificial Intelligence Clients Speak Like Human Clients? Exploring GPT‐4’s Content‐Level Performance in Counseling Role‐Play Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study explores the use of GPT‐4, a large language model (LLM) with voice capabilities, for client simulation in counseling role‐play practices. |
XIHE TIAN et. al. | Journal of Counseling & Development | 2025-11-05 |
| 528 | Chronic Kidney Disease Prognosis Prediction Using Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present atransformer-based framework for predicting CKD progression using multi-modalelectronic health records (EHR) from the Seoul National University HospitalOMOP Common Data Model. |
Yohan Lee; DongGyun Kang; SeHoon Park; Sa-Yoon Park; Kwangsoo Kim; | arxiv-cs.AI | 2025-11-04 |
| 529 | No-Human in The Loop: Agentic Evaluation at Scale for Recommendation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Evaluating large language models (LLMs) as judges is increasingly criticalfor building scalable and trustworthy evaluation pipelines. |
TAO ZHANG et. al. | arxiv-cs.AI | 2025-11-04 |
| 530 | Prompting for Policy: Forecasting Macroeconomic Scenarios with Synthetic LLM Personas Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We evaluate whether persona-based prompting improves Large Language Model(LLM) performance on macroeconomic forecasting tasks. |
Giulia Iadisernia; Carolina Camassa; | arxiv-cs.CL | 2025-11-04 |
| 531 | Targeted Error Correction in Knowledge Distillation: Small Language Models Surpass GPT Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce an Analyze-Revise-Finetune (ARF) pipeline that enables smalleropen-source language models (LLMs) to surpass substantially larger proprietarymodels in customer service summarization tasks. |
Hee-Jin Lee; Zhen Guo; Luchao Jin; Morteza Moazami Goudarzi; | arxiv-cs.CL | 2025-11-04 |
| 532 | A Survey of Adaptation of Large Language Models to Idea and Hypothesis Generation: Downstream Task Adaptation, Knowledge Distillation Approaches and Challenges Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this study, systematic literature review is carried out to provide understanding on how LLMs have been applied to the classical downstream tasks and to then motivate adaptation of LLMs to idea and hypothesis generation. |
Olaide N Oyelade; Hui Wang; Karen Rafferty; | ACM Computing Surveys | 2025-11-04 |
| 533 | Transcription Accuracy of Automatic Speech Recognition for Orthodontic Clinical Records Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The aim of this study was to investigate the transcriptional accuracy of ASR systems using orthodontic clinical records as the experimental model. |
R. O’KANE et. al. | Journal of Dental Research | 2025-11-03 |
| 534 | LLMs As Judges: Toward The Automatic Review of GSN-compliant Assurance Cases Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, assurance cases often tendto be organized as extensive documents spanning hundreds of pages, making theircreation, review, and maintenance error-prone, time-consuming, and tedious.Therefore, there is a growing need to leverage (semi-)automated techniques,such as those powered by generative AI and large language models (LLMs), toenhance efficiency, consistency, and accuracy across the entire assurance-caselifecycle. In this paper, we focus on assurance case review, a critical taskthat ensures the quality of assurance cases and therefore fosters theiracceptance by regulatory authorities. |
GERHARD YU et. al. | arxiv-cs.SE | 2025-11-03 |
| 535 | Abstract 4369198: Performance of Large Language Models in Analyzing Common Hypertension Scenarios in Clinical Practice Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study evaluated the accuracy and safety of hypertension management recommendations generated by three LLMs compared to expert responses. |
JALEH ZAND et. al. | Circulation | 2025-11-03 |
| 536 | Restaurant Review Sentiment and SWOT Analysis: Using AWS and GPT-4 Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save |
Mustafa Demirbilek; Sevim Özulukale Demirbilek; | Acta Infologica | 2025-11-03 |
| 537 | Foundations of Domain-specific Large Language Models for Islamic Studies: A Comprehensive Review Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This article reviews the evolution of neural language models by comparing the historical progression of general LLMs with emerging Islamic-specific LLMs. |
Mohamed Yassine El Amrani; Arshad Vakayil; Feroz Mohammed; Faisal Al Amri; | Journal of ICT Research and Applications | 2025-11-03 |
| 538 | Evaluating GPT-4’s Ability to Generate Informed Consent Material for Genetic Testing Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: GPT-4 performed well on structured components, such as explaining the purpose and benefits of testing, but struggled with nuanced ethical and contextual content. |
EIRINI PETROU et. al. | npj Artificial Intelligence | 2025-11-03 |
| 539 | Prompt Injection As An Emerging Threat: Evaluating The Resilience of Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study proposes a unified framework for evaluating howresistant Large Language Models (LLMs) are to prompt injection attacks. |
Daniyal Ganiuly; Assel Smaiyl; | arxiv-cs.CR | 2025-11-03 |
| 540 | Math Anxiety and Associative Knowledge Structure Are Entwined in Psychology Students But Not in Large Language Models Like GPT-3.5 and GPT-4o Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study employs aframework based on behavioural forma mentis networks (i.e. cognitive modelsthat map how individuals structure their associative knowledge and emotionalperceptions of concepts) to explore individual and group differences in theperception and association of concepts related to math and anxiety. |
LUCIANA CIRINGIONE et. al. | arxiv-cs.CL | 2025-11-03 |
| 541 | Abstract 4366575: Performance Benchmarking of Smaller Language Models Against GPT-4 for Predicting Reasons for Oral Anticoagulation Nonprescription in Atrial Fibrillation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We investigate whether smaller, open-source LLMs (Gemma-2-9B-IT, Phi-4K) can achieve comparable performance. |
SULAIMAN SOMANI et. al. | Circulation | 2025-11-03 |
| 542 | Abstract Sat906: Using Natural Language Processing to Distinguish Recalled Experiences of Death from Drug-Induced Hallucinations and Dreams in Cardiac Arrest and Critical Ill Survivors Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: As Natural Language Processing (NLP) – a scalable and reproducible method that enables systematic analysis of unstructured, self-reported data, allowing pattern recognition beyond subjective interpretation – we sought to determine whether RED may be objectively distinguished from dreams, and drug-induced states. |
SANAM ALILOU et. al. | Circulation | 2025-11-03 |
| 543 | Performance of Large Language Models in Analyzing Common Hypertension Scenarios Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study evaluated the accuracy and safety of hypertension management recommendations generated by 3 LLMs. |
JALEH ZAND et. al. | Hypertension | 2025-11-03 |
| 544 | IIET: Efficient Numerical Transformer Via Implicit Iterative Euler Method Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: High-order numerical methods enhance Transformer performance in tasks like NLP and CV, but introduce a performance-efficiency trade-off due to increased computational overhead. |
XINYU LIU et. al. | emnlp | 2025-11-02 |
| 545 | Speculating LLMs’ Chinese Training Data Pollution from Their Tokens Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: 1/o4-mini) are indicating contents like pornography or online gambling. Based on this observation, our goal is to locate Polluted Chinese (PoC) tokens in LLMs and study the relationship between PoC tokens’ existence and training data. |
QINGJIE ZHANG et. al. | emnlp | 2025-11-02 |
| 546 | AdamS: Momentum Itself Can Be A Normalizer for LLM Pretraining and Post-training Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: We introduce AdamS, a simple yet effective alternative to Adam for large language model (LLM) pretraining and post-training. |
Huishuai Zhang; Bohan Wang; Luoxin Chen; | emnlp | 2025-11-02 |
| 547 | Spectral Neuro-Symbolic Reasoning II: Semantic Node Merging, Entailment Filtering, and Knowledge Graph Alignment Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This report extends the Spectral Neuro-Symbolic Reasoning (Spectral NSR) framework by introducing three semantically grounded enhancements: (1) transformer-based node merging using contextual embeddings (e.g., Sentence-BERT, SimCSE) to reduce redundancy, (2) sentence-level entailment validation with pretrained NLI classifiers (e.g., RoBERTa, DeBERTa) to improve edge quality, and (3) alignment with external knowledge graphs (e.g., ConceptNet, Wikidata) to augment missing context. |
Andrew Kiruluta; Priscilla Burity; | arxiv-cs.CL | 2025-11-02 |
| 548 | Table-LLM-Specialist: Language Model Specialists for Tables Using Iterative Fine-tuning Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we propose Table-Specialist, a new self-trained fine-tuning paradigm specifically designed for table tasks. |
JUNJIE XING et. al. | emnlp | 2025-11-02 |
| 549 | OntologyRAG-Q: Resource Development and Benchmarking for Retrieval-Augmented Question Answering in Qur’anic Tafsir Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present a comprehensive framework for handling sensitive Qur’anic Tafsir data that spans the entire pipeline from dataset construction through evaluation and error analysis. |
Sadam Al-Azani; Maad Alowaifeer; Alhanoof Alhunief; Ahmed Abdelali; | emnlp | 2025-11-02 |
| 550 | Discursive Circuits: How Do Language Models Understand Discourse Relations? Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To make circuit discovery feasible, we introduce a task called Completion under Discourse Relation (CuDR), where a model completes a discourse given a specified relation. |
Yisong Miao; Min-Yen Kan; | emnlp | 2025-11-02 |
| 551 | Training Compute-optimal Transformer Encoder Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present the first comprehensive empirical investigation of compute-optimal pretraining for encoder transformers using the Masked Language Modeling (MLM) objective. |
Megi Dervishi; Alexandre Allauzen; Gabriel Synnaeve; Yann LeCun; | emnlp | 2025-11-02 |
| 552 | Large Language Models and Futures Price Factors in China Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: ABSTRACT We leverage the capacity of large language models such as Generative Pre‐trained Transformer (GPT) in constructing factor models for Chinese futures markets. |
Yuhan Cheng; Yanchu Liu; Heyang Zhou; | Journal of Futures Markets | 2025-11-02 |
| 553 | Trojsten Benchmark: Evaluating LLM Problem-Solving in Slovak STEM Competition Problems Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce Trojsten Benchmark, a Slovak-language dataset of 1,108 high-school competition problems with reference solutions across mathematics, physics, and programming, and a rubric-based LLM grading framework. |
Adam Zahradník; Marek Suppa; | emnlp | 2025-11-02 |
| 554 | Assessing Effective De-escalation of Crisis Conversations Using Transformer-based Models and Trend Statistics Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Accordingly, we developed a transformer-based emotional valence scoring model fit for crisis conversations, BERT-EV, that assigns numerical emotional valence scores to rate the intensity of expressed negative versus positive emotion. |
Ignacio J. Tripodi; Greg Buda; Margaret Meagher; Elizabeth A. Olson; | emnlp | 2025-11-02 |
| 555 | Improving Cross Lingual Transfer By Pretraining with Active Forgetting Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we propose a pretraining strategy that uses active forgetting to achieve similar cross lingual transfer in decoder-only LLMs. |
Divyanshu Aggarwal; Ashutosh Sathe; Sunayana Sitaram; | emnlp | 2025-11-02 |
| 556 | Evaluating The Efficacy of A Large Language Model in Scaffolding Research Report Writing for EFL Learners Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study examines how the Generative Pre-trained Transformer (GPT) architecture can assist English as a Foreign Language (EFL) learners in writing research reports. |
Taj Mohammad; Mohd Nazim; Ali Abbas Falah Alzubi; Soada Idris Khan; | International Journal of Basic and Applied Sciences | 2025-11-02 |
| 557 | Can Large Language Models Unlock Novel Scientific Research Ideas? IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: This study explores the capability of LLMs in generating novel research ideas based on information from research papers. |
Sandeep Kumar; Tirthankar Ghosal; Vinayak Goyal; Asif Ekbal; | emnlp | 2025-11-02 |
| 558 | SCRIBE: Structured Chain Reasoning for Interactive Behaviour Explanations Using Tool Calling Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce SCRIBE, a framework for multi-hop, tool-augmented reasoning designed to generate valid responses to student questions about feedback reports. |
Fares Fawzi; Vinitra Swamy; Dominik Glandorf; Tanya Nazaretsky; Tanja Käser; | emnlp | 2025-11-02 |
| 559 | A Generative Pre-Trained Language Model for Channel Prediction in Wireless Communications Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we formulate the ‘channel sentence’ based on channel correlation, where the channel is regarded as a ‘word’. |
BO LIN et. al. | emnlp | 2025-11-02 |
| 560 | DINT Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, this architecture suffers from two major limitations: first, its use of two independent attention matrices leads to numerical instability, and second, it lacks global context modeling, which is essential for identifying globally significant tokens. To address these challenges, we propose the DINT Transformer, which extends the DIFF Transformer by incorporating an integral mechanism. |
Yueyang Cang; Yuhang Liu; Xiaoteng Zhang; Erlu Zhao; Li Shi; | emnlp | 2025-11-02 |
| 561 | PPC-GPT: Federated Task-Specific Compression of Large Language Models Via Pruning and Chain-of-Thought Distillation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Compressing Large Language Models (LLMs) into task-specific Small Language Models (SLMs) encounters two significant challenges: safeguarding domain-specific knowledge privacy and managing limited resources. To tackle these challenges, we propose PPC-GPT, a novel unified framework that systematically addresses both privacy preservation and model compression in federated settings. |
Tao Fan; Guoqiang Ma; Yuanfeng Song; Lixin Fan; Qiang Yang; | emnlp | 2025-11-02 |
| 562 | Do All Autoregressive Transformers Remember Facts The Same Way? A Cross-Architecture Analysis of Recall Mechanisms Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, it remains unclear whether these findings generalize across different autoregressive architectures. To address this, we conduct a comprehensive evaluation of factual recall across several models—including GPT, LLaMA, Qwen, and DeepSeek—analyzing where and how factual information is encoded and accessed. |
Minyeong Choe; Haehyun Cho; Changho Seo; Hyunil Kim; | emnlp | 2025-11-02 |
| 563 | Integral Transformer: Denoising Attention, Not Too Much Not Too Little Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we propose the Integral Transformer, a novel self-attention mechanism that denoises attention by integrating signals sampled from the logit distribution. |
Ivan Kobyzev; Abbas Ghaddar; Dingtao Hu; Boxing Chen; | emnlp | 2025-11-02 |
| 564 | Mixture of Languages: Improved Multilingual Encoders Through Language Grouping Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose Mixture of Languages (MoL), a new strategy to pretrain largely multilingual encoders. |
JOÃO MARIA JANEIRO et. al. | emnlp | 2025-11-02 |
| 565 | Detecting Legal Citations in United Kingdom Court Judgments Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Extracting references to legislation and case law in the United Kingdom is especially challenging: citation styles have evolved over centuries, and judgments routinely cite foreign or historical authorities. We conduct the first systematic comparison of three modelling paradigms on this task using the Cambridge Law Corpus: (i) rule‐based regular expressions; (ii) transformer-based encoders (BERT, RoBERTa, LEGAL‐BERT, ModernBERT); and (iii) large language models (GPT‐4. |
Holli Sargeant; Andreas Östling; Måns Magnusson; | emnlp | 2025-11-02 |
| 566 | Exploring and Mitigating Gender Bias in Encoder-Based Transformer Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To quantify the degree of bias, we introduce a novel metric,MALoR, which assesses bias based on model probabilities for filling maskedtokens. |
ARIYAN HOSSAIN et. al. | arxiv-cs.CL | 2025-11-01 |
| 567 | Enhancing Autonomous Driving Simulations: A Hybrid Metamorphic Testing Framework with Metamorphic Relations Generated By GPT Related Papers Related Patents Related Grants Related Venues Related Experts View Save |
YIFAN ZHANG et. al. | Inf. Softw. Technol. | 2025-11-01 |
| 568 | LLM4Schema.org: Generating Schema.org Markups With Large Language Models Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Integrating Schema.org markup into web pages has resulted in the generation of billions of RDF triples. However, around 75% of web pages still lack this critical markup. Large … |
M. Dang; Thi Hoang Thi Pham; P. Molli; Hala Skaf-Molli; Alban Gaignard; | Semantic Web | 2025-11-01 |
| 569 | A Novel Approach for Malicious URL Detection Using RoBERTa and Sparse Autoencoder Related Papers Related Patents Related Grants Related Venues Related Experts View Save |
Zhiqing Huang; Tian Ban; Yanxin Zhang; | J. Inf. Secur. Appl. | 2025-11-01 |
| 570 | Leveraging Large Language Model for Generalization in Building Energy Management Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Buildings are major contributors to global electricity consumption and emission, making the development of effective Building Energy Management Systems (BEMS) essential for … |
MINGHUI ZHANG et. al. | IEEE Transactions on Smart Grid | 2025-11-01 |
| 571 | Style Mamba-transformer: A Hybrid Mamba-transformer Unsupervised Framework for Text Style Transfer Related Papers Related Patents Related Grants Related Venues Related Experts View Save |
Deyu Meng; Ziheng Wang; Wenhao Yan; Tshewang Phuntsho; Tad Gonsalves; | Knowl. Based Syst. | 2025-11-01 |
| 572 | Performance of Generative Artificial Intelligence Models (GPT-4o, Gemini, Copilot) in YKS/TYT Exam: A Comparative Study Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In the study, GPT, Gemini and Copilot models were tested with questions in the Higher Education Institutions Exam (YKS)/ Basic Proficiency Exam ( TYT) session in Turkey. |
Selma Bulut; | Bilişim Teknolojileri Dergisi | 2025-10-31 |
| 573 | Cognitively-Inspired Episodic Memory Architectures for Accurate and Efficient Character AI Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Large language models show promise for embodying historical characters in dialogue systems, but existing approaches face a critical trade-off: simple retrieval-augmented generation produces shallow responses, while multi-stage reflection achieves depth at prohibitive latency. We present an architecture that resolves this tension through offline data augmentation and efficient parallel retrieval from structured episodic memory. |
Rafael Arias Gonzalez; Steve DiPaola; | arxiv-cs.CL | 2025-10-31 |
| 574 | A Study on How LLMs (e.g. GPT-4, Chatbots) Are Being Integrated to Support Tutoring, Essay Feedback and Content Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Through a combination of multiple dimensions, such as adaptive tutoring, personalized feedback, and generative lesson design, the paper clarifies the opportunities and challenges of implementing the use of LLMs in teaching practice. |
Nhu Tam Mai; Wenyang Cao; Qianyi Fang; | Journal of Computing and Electronic Information Management | 2025-10-30 |
| 575 | Enhancing Sentiment Classification with Machine Learning and Combinatorial Fusion Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents a novel approach to sentiment classification using theapplication of Combinatorial Fusion Analysis (CFA) to integrate an ensemble ofdiverse machine learning models, achieving state-of-the-art accuracy on theIMDB sentiment analysis dataset of 97.072\%. |
Sean Patten; Pin-Yu Chen; Christina Schweikert; D. Frank Hsu; | arxiv-cs.LG | 2025-10-30 |
| 576 | A Multi-agent Large Language Model Framework to Automatically Assess Performance of A Clinical AI Triage Tool Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Purpose: The purpose of this study was to determine if an ensemble ofmultiple LLM agents could be used collectively to provide a more reliableassessment of a pixel-based AI triage tool than a single LLM. |
ADAM E. FLANDERS et. al. | arxiv-cs.CL | 2025-10-30 |
| 577 | Simulating and Experimenting with Social Media Mobilization Using LLM Agents Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Building on the landmark 61-million-personFacebook experiment \citep{bond201261}, we develop an agent-based simulationframework that integrates real U.S. Census demographic distributions, authenticTwitter network topology, and heterogeneous large language model (LLM) agentsto examine the effect of mobilization messages on voter turnout. |
Sadegh Shirani; Mohsen Bayati; | arxiv-cs.SI | 2025-10-30 |
| 578 | Who Has The Final Say? Conformity Dynamics in ChatGPT’s Selections Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Large language models (LLMs) such as ChatGPT are increasingly integrated intohigh-stakes decision-making, yet little is known about their susceptibility tosocial influence. |
Clarissa Sabrina Arlinghaus; Tristan Kenneweg; Barbara Hammer; Günter W. Maier; | arxiv-cs.AI | 2025-10-30 |
| 579 | EdgeRunner 20B: Military Task Parity with GPT-5 While Running on The Edge Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present EdgeRunner 20B, a fine-tuned version of gpt-oss-20b optimized formilitary tasks. |
JACK FITZGERALD et. al. | arxiv-cs.AI | 2025-10-30 |
| 580 | Analysing The Role of LLMs in Cybersecurity Incident Management Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Our work explores the effectiveness of generative AI, specifically Large Language Models (LLMs), within cybersecurity, focusing primarily on incident response processes. |
Gavin Jones; Dimitrios Kasimatis; Nikolaos Pitropakis; Richard Macfarlane; William J. Buchanan; | International Journal of Information Security | 2025-10-30 |
| 581 | Financial Sentiment Analysis with FUNNEL: Filtered UNion for NER-based Ensemble Labeling Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Abstract This paper introduces FUNNEL (Filtered UNion for NER-based Ensemble Labeling), a novel ensemble-based framework for labeling financial news that enhances the reliability of stock-specific sentiment signals. |
William Nordansjö; Fredrik Fourong; Muhammad Qasim; | Digital Finance | 2025-10-30 |
| 582 | Context‐Aware Prompt Engineering for Large Language Models in Autonomous Vehicles Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: ABSTRACT This paper presents a soft and novel context‐aware prompt engineering framework to enable adaptive and safe integration of large language models (LLMs) into autonomous vehicle (AV) systems. |
Shirin Abbasi; Amir Masoud Rahmani; | Concurrency and Computation: Practice and Experience | 2025-10-29 |
| 583 | Detecting Laterality Errors in Combined Radiographic Studies By Enhancing The Traditional Approach With GPT-4o: Algorithm Development and Multisite Internal Validation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Third, we demonstrate significant performance gaps between real-world imbalanced and synthetic balanced datasets, highlighting limitations of the benchmarking methodology commonly used in current studies. Methods This retrospective study analyzed deidentified English radiology reports containing laterality terms in order. |
Kung-Hsun Weng; Yi-Chen Chou; Yu-Ting Kuo; Tsyh-Jyi Hsieh; Chung-Feng Liu; | JMIR Formative Research | 2025-10-29 |
| 584 | Humains-Junior: A 3.8B Language Model Achieving GPT-4o-Level Factual Accuracy By Directed Exoskeleton Reasoning Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce Humans-Junior, a 3.8B model that matches GPT-4o on the FACTSGrounding public subset within a $\pm 5$ pp equivalence margin. |
Nissan Yaron; Dan Bystritsky; Ben-Etzion Yaron; | arxiv-cs.AI | 2025-10-29 |
| 585 | Advancing Urdu Named Entity Recognition: Deep Learning for Aspect Targeting Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We meticulously developed a comprehensive corpus from diverse news sources, specifically tailored to reflect Urdu’s unique orthographic and morphological characteristics. |
KAMRAN AZIZ et. al. | Complex & Intelligent Systems | 2025-10-29 |
| 586 | MODEL OF COMMUNICATIVE IMPACT IN DISINFORMATION MESSAGES BASED ON SPEECH ACT THEORY AND ARTIFICIAL INTELLIGENCE TOOLS Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The present article explores the communicative impact of disinformation messages by combining the theoretical framework of speech act theory with the analytical capabilities of artificial intelligence (AI). |
Oleksandr Cherep; Yuliia Kaliuzhna; Svitlana Markova; | Baltic Journal of Economic Studies | 2025-10-29 |
| 587 | Standardization of Psychiatric Diagnoses – Role of Fine-tuned LLM Consortium and OpenAI-gpt-oss Reasoning LLM Enabled Decision Support System Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The diagnosis of most mental disorders, including psychiatric evaluations, primarily depends on dialogues between psychiatrists and patients. This subjective process can lead to … |
ERANGA BANDARA et. al. | ArXiv | 2025-10-29 |
| 588 | Standardization of Psychiatric Diagnoses — Role of Fine-tuned LLM Consortium and OpenAI-gpt-oss Reasoning LLM Enabled Decision Support System Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose a novel methodfor deploying LLM agents that orchestrate communication between the LLMconsortium and the reasoning LLM, ensuring transparency, reliability, andresponsible AI across the entire diagnostic workflow. |
ERANGA BANDARA et. al. | arxiv-cs.AI | 2025-10-29 |
| 589 | A Systematic Review and Meta-analysis of GPT-based Differential Diagnostic Accuracy in Radiological Cases: 2023–2025 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Methods A systematic review and meta-analysis were conducted using PubMed and SCOPUS databases on March 24, 2025, retrieving 639 articles. |
Daniel Nguyen; Isaac Bronson; Ryan Chen; Young H. Kim; | Frontiers in Radiology | 2025-10-28 |
| 590 | DynBERG: Dynamic BERT-based Graph Neural Network for Financial Fraud Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, financial transaction networks are inherently dynamic, withevolving structures and directed edges representing the flow of money. Toaddress these challenges, we introduce DynBERG, a novel architecture thatintegrates Graph-BERT with a Gated Recurrent Unit (GRU) layer to capturetemporal evolution over multiple time steps. |
Omkar Kulkarni; Rohitash Chandra; | arxiv-cs.LG | 2025-10-28 |
| 591 | Aspect-Based Sentiment Analysis for Turkish Reviews Using Token and Sequential Classification Methods Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Hence, developing sentiment analysis approaches tailored to Turkish is of significant importance. We propose a two-stage pipeline: a token-level classification to recognize aspect terms and assign them to one of 12 predefined aspect categories, followed by a sequence-level (sentence-level) classification to predict sentiment (positive, negative, or neutral) for each identified aspect. |
Metin Bilgin; Melek Turan; | International Journal of Computer and Information … | 2025-10-28 |
| 592 | ComboBench: Can LLMs Manipulate Physical Devices to Play Virtual Reality Games? Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We evaluate seven LLMs, including GPT-3.5, GPT-4, GPT-4o,Gemini-1.5-Pro, LLaMA-3-8B, Mixtral-8x7B, and GLM-4-Flash, compared againstannotated ground truth and human performance. |
SHUQING LI et. al. | arxiv-cs.CL | 2025-10-28 |
| 593 | Multi-Aspect Temporal Topic Evolution with Neural-Symbolic Fusion and Information Extraction for Yelp Review Analysis: A Comprehensive Deep Learning Framework Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose the MultiAspect Temporal Topic Evolution with NeuralSymbolic Fusion and Information Extraction (MATTE-NSF-IE) framework, a novel end-to-end system for analysing restaurant reviews. |
Irfan Ali; | Indian Journal of Artificial Intelligence and Neural … | 2025-10-28 |
| 594 | Evaluating LLMs on Generating Age-Appropriate Child-Like Conversations Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present a comparative studyevaluating five different LLMs (GPT-4, RUTER-LLAMA-2-13b, GPTSW, NorMistral-7b,and NorBloom-7b) to generate age-appropriate Norwegian conversations forchildren aged 5 and 9 years. |
Syed Zohaib Hassan; Pål Halvorsen; Miriam S. Johnson; Pierre Lison; | arxiv-cs.CL | 2025-10-28 |
| 595 | GPT-ReID: Learning Fine-grained Representation with GPT for Text-based Person Retrieval Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Motivated by the recent progress of large language models (LLMs), we propose a novel method named GPT-ReID for TBPR, which aims to leverage the strong comprehension of LLMs to alleviate the overfitting risk. |
Xudong Wang; Lei Tan; Pingyang Dai; Liujuan Cao; Rongrong Ji; | mm | 2025-10-27 |
| 596 | LLMs As Mediators: Can They Diagnose Conflicts Accurately? Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We use a vignette study to apply the test to OpenAI’s GPT-3.5 and GPT-4. |
Özgecan Koçak; Phanish Puranam; AFSAR YEGIN; | ACM Journal on Computing and Sustainable Societies | 2025-10-27 |
| 597 | TimesBERT: A BERT-Style Foundation Model for Time Series Understanding Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, inspired by the shared multi-granularity structure between multivariate time series and multisentence documents, we design TimesBERT to learn generic representations of time series including temporal patterns and variate-centric characteristics. |
HAORAN ZHANG et. al. | mm | 2025-10-27 |
| 598 | Text to Trust: Evaluating Fine-Tuning and LoRA Trade-offs in Language Models for Unfair Terms of Service Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study provides a systematic evaluation of fine tuning,parameter efficient adaptation (LoRA, QLoRA), and zero-shot promptingstrategies for unfair clause detection in Terms of Service (ToS) documents, akey application in legal NLP. |
Noshitha Padma Pratyusha Juttu; Sahithi Singireddy; Sravani Gona; Sujal Timilsina; | arxiv-cs.CL | 2025-10-26 |
| 599 | Evaluating Large Language Models for Turboshaft Engine Torque Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Through this analysis, we aim to better understand how language models can be effectively adapted to |
Alessandro Tronconi; David He; Eric Bechhoefer; | Annual Conference of the PHM Society | 2025-10-26 |
| 600 | Integration of LLMs for Multitasking Workload Prediction in Mixed Reality Environments Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study proposes a novel framework that integrates large language models (LLMs) with traditional workload assessment tools to enhance prediction accuracy in MR multitasking scenarios. |
Safanah Abbas; Heejin Jeong; David He; | Annual Conference of the PHM Society | 2025-10-26 |
| 601 | Supervised Fine-Tuning or In-Context Learning? Evaluating LLMs for Clinical NER Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We study clinical Named Entity Recognition (NER) on the CADEC corpus andcompare three families of approaches: (i) BERT-style encoders (BERT Base,BioClinicalBERT, RoBERTa-large), (ii) GPT-4o used with few-shot in-contextlearning (ICL) under simple vs.\ complex prompts, and (iii) GPT-4o withsupervised fine-tuning (SFT). |
Andrei Baroian; | arxiv-cs.CL | 2025-10-25 |
| 602 | Irony Detection in Urdu Text: A Comparative Study Using Machine Learning Models and Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we aim to detect irony in Urdu by translating an EnglishIronic Corpus into the Urdu language. |
FIAZ AHMAD et. al. | arxiv-cs.CL | 2025-10-25 |
| 603 | Memory-based Language Models: An Efficient, Explainable, and Eco-friendly Approach to Large Language Modeling Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present memory-based language modeling as an efficient, eco-friendlyalternative to deep neural network-based language modeling. |
Antal van den Bosch; Ainhoa Risco Patón; Teun Buijse; Peter Berck; Maarten van Gompel; | arxiv-cs.CL | 2025-10-25 |
| 604 | You Don’t Need Prompt Engineering Anymore: The Prompting Inversion Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce Sculpting, aconstrained, rule-based prompting method designed to improve upon standard CoTby reducing errors from semantic ambiguity and flawed common sense. |
Imran Khan; | arxiv-cs.CL | 2025-10-25 |
| 605 | InterpDetect: Interpretable Signals for Detecting Hallucinations in Retrieval-Augmented Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We investigate the mechanisms underlying RAG hallucinationsand find they arise when later-layer FFN modules disproportionately injectparametric knowledge into the residual stream. To address this, we explore amechanistic detection approach based on external context scores and parametricknowledge scores. |
Likun Tan; Kuan-Wei Huang; Joy Shi; Kevin Wu; | arxiv-cs.CL | 2025-10-24 |
| 606 | Jailbreak Mimicry: Automated Discovery of Narrative-Based Jailbreaks for Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Developed for theOpenAI GPT-OSS-20B Red-Teaming Challenge, we use parameter-efficientfine-tuning (LoRA) on Mistral-7B with a curated dataset derived from AdvBench,achieving an 81.0% Attack Success Rate (ASR) against GPT-OSS-20B on a held-outtest set of 200 items. |
Pavlos Ntais; | arxiv-cs.CR | 2025-10-24 |
| 607 | HalleluBERT: Let Every Token That Has Meaning Bear Its Weight Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present HalleluBERT, a RoBERTa-based encoder family (baseand large) trained from scratch on 49.1~GB of deduplicated Hebrew web text andWikipedia with a Hebrew-specific byte-level BPE vocabulary. |
Raphael Scheible-Schmitt; | arxiv-cs.CL | 2025-10-24 |
| 608 | SindBERT, The Sailor: Charting The Seas of Turkish NLP Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: WithSindBERT, we set out to chart the seas of Turkish NLP, providing the firstlarge-scale RoBERTa-based encoder for Turkish. |
Raphael Scheible-Schmitt; Stefan Schweter; | arxiv-cs.CL | 2025-10-24 |
| 609 | A Comprehensive Survey on Transformer-Based Machine Translation: Identifying Research Gaps and Solutions for Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper handles the key challenges in transformer-based architectures for machine translation, proposing solutions to specific issues and highlighting areas where researchers can focus on bridging existing gaps, thereby reducing the effort needed to identify research opportunities. |
Anasua Banerjee; Dr. Debajyoty Banik; | ACM Computing Surveys | 2025-10-24 |
| 610 | Peningkatan Kompetensi Guru Melalui Pelatihan Penggunaan Teknologi AI (GPT) Dalam Pengembangan Bahan Ajar Digital Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: This community service program was carried out with the aim of enhancing teachers’ competencies in utilizing Artificial Intelligence technology, particularly the Generative … |
Fitriana Harahap; Husin Sariangsah; Hanafi Asnan; Masri Wahyuni; Joko Eriyanto; | ARDHI : Jurnal Pengabdian Dalam Negri | 2025-10-23 |
| 611 | A Coherence-Based Measure of AGI Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose a coherence-aware measure of AGI based on the integral ofgeneralized means over a continuum of compensability exponents. |
Fares Fourati; | arxiv-cs.AI | 2025-10-23 |
| 612 | BUSTED at AraGenEval Shared Task: A Comparative Study of Transformer-Based Models for Arabic AI-Generated Text Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper details our submission to the Ara- GenEval Shared Task on ArabicAI-generated text detection, where our team, BUSTED, se- cured 5th place. |
Ali Zain; Sareem Farooqui; Muhammad Rafi; | arxiv-cs.CL | 2025-10-23 |
| 613 | Comparing KNN, Logistic Regression, Random Forest and BERT Fine-Tuning for Scam Message Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study compares the effectiveness of conventional classifiers—K-Nearest Neighbors (KNN), Logistic Regression, and Random Forest—using frozen BERT embeddings, against a fully fine-tuned BERT model trained end-to-end. |
Tianyi Xie; | Finance & Economics | 2025-10-23 |
| 614 | A Review of The Application of Transformer in Financial Market Risk Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This review summarizes the application of the Transformer model in financial market risk prediction and adopts data from Wanfang Database and the National Philosophy and Social Sciences Literature Center. |
Lewei Yu; | Finance & Economics | 2025-10-23 |
| 615 | Forging GEMs: Advancing Greek NLP Through Quality-Based Corpus Curation and Specialized Pre-training Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This is particularly true in specialized,high-value domains such as law, where existing models are frequently confinedto early transformer architectures with a restrictive 512-token window,insufficient for analyzing long legal documents. To address these challenges,this paper presents Greek Embedding Models, a new family of transformer modelsfor Greek language built upon a foundation of extensive, quality-driven datacuration. |
ALEXANDRA APOSTOLOPOULOU et. al. | arxiv-cs.CL | 2025-10-22 |
| 616 | Cultural Alien Sampler: Open-ended Art Generation Balancing Originality and Coherence Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In open-ended domains like art, autonomous agents must generate ideas thatare both original and internally coherent, yet current Large Language Models(LLMs) either default to familiar cultural patterns or sacrifice coherence whenpushed toward novelty. We address this by introducing the Cultural AlienSampler (CAS), a concept-selection method that explicitly separatescompositional fit from cultural typicality. |
ALEJANDRO H. ARTILES et. al. | arxiv-cs.AI | 2025-10-21 |
| 617 | Misinformation Detection Using Large Language Models with Explainability Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Thiswork makes two key contributions: (1) it quantitatively shows that alightweight PLM can maintain task performance while substantially reducingcomputational cost, and (2) it presents an explainable pipeline that retrievesfaithful local and global justifications without compromising performance. |
Jainee Patel; Chintan Bhatt; Himani Trivedi; Thanh Thi Nguyen; | arxiv-cs.CL | 2025-10-21 |
| 618 | Exploration of Stability Judgments: Assessing Multimodal LLMs in Game-Inspired Physical Reasoning Tasks Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Human participants were included as a reference point, consistently achieving the highest accuracy, underscoring the gap between model and human performance. Among MLLMs, the GPT series continued to perform strongly, with GPT-4o showing reliable results in image-based tasks, while the Qwen2.5-VL series reached the highest overall scores in this extended study and in some cases surpassed commercial counterparts. |
MURY FAJAR DEWANTORO et. al. | Applied Sciences | 2025-10-21 |
| 619 | Explainable Bilingual Medical-Question-Answering Model Using Ensemble Learning Technique Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study establishes a foundation for building multilingual healthcare information systems, promoting inclusive and equitable access to medical information. |
Abdul Rahaman Wahab Sait; Yazeed Alkhurayyif; | Electronics | 2025-10-21 |
| 620 | A Graph Signal Processing Framework for Hallucination Detection in Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Large language models achieve impressive results but distinguishing factualreasoning from hallucinations remains challenging. We propose a spectralanalysis framework that models transformer layers as dynamic graphs induced byattention, with token embeddings as signals on these graphs. |
Valentin Noël; | arxiv-cs.CL | 2025-10-21 |
| 621 | TAR3D: Creating High-Quality 3D Assets Via Next-Part Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present TAR3D, a novel framework that consists of a 3D-aware Vector Quantized-Variational AutoEncoder (VQVAE) and a Generative Pre-trained Transformer (GPT) to generate high-quality 3D assets. |
XUYING ZHANG et. al. | iccv | 2025-10-20 |
| 622 | Chain-of-Thought Reasoning Improves Context-Aware Translation with Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper assesses the capacity of large language models (LLMs) to translatetexts that include inter-sentential dependencies. |
Shabnam Ataee; Andrei Popescu-Belis; | arxiv-cs.CL | 2025-10-20 |
| 623 | Scene Graph Guided Generation: Enable Accurate Relations Generation in Text-to-Image Models Via Textural Rectification Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we introduce the Scene Graph Adapter(SG-Adapter), leveraging the structured representation of scene graphs to rectify inaccuracies in the original text embeddings. |
GUIBAO SHEN et. al. | iccv | 2025-10-20 |
| 624 | Transformer-Based Low-Resource Language Translation: A Study on Standard Bengali to Sylheti Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Machine Translation (MT) has advanced from rule-based and statistical methods to neural approaches based on the Transformer architecture. While these methods have achieved … |
Mangsura Kabir Oni; Tabia Tanzin Prama; | ArXiv | 2025-10-20 |
| 625 | An Enhanced Dual Transformer Contrastive Network for Multimodal Sentiment Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To furtherenhance the model’s capability, we propose an extension called the DualTransformer Contrastive Network (DTCN), which builds upon BERT-ViT-EF. |
Phuong Q. Dao; Mark Roantree; Vuong M. Ngo; | arxiv-cs.LG | 2025-10-20 |
| 626 | HIS-GPT: Towards 3D Human-In-Scene Multimodal Understanding Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose a new task to benchmark human-in-scene understanding for embodied agents: Human-In-Scene Question Answering (HIS-QA). |
Jiahe Zhao; Ruibing Hou; Zejie Tian; Hong Chang; Shiguang Shan; | iccv | 2025-10-20 |
| 627 | Predicting Software Developer Sentiment on Self-admitted Technical Debt Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Empirical results show that, compared with a set of traditional machine learning and deep learning techniques, the fine-tuning GPT-3.5-turbo model improves the evaluation indicators precision, recall and F1-score by 14.2%, 11.5%, and 17.3%, respectively. |
HAICHUAN ZHANG et. al. | PeerJ Computer Science | 2025-10-20 |
| 628 | MEG-GPT: A Transformer-based Foundation Model for Magnetoencephalography Data Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This work establishes a powerful foundationmodel for electrophysiological data, paving the way for applications incomputational neuroscience and neural decoding. |
Rukuang Huang; Sungjun Cho; Chetan Gohil; Oiwi Parker Jones; Mark Woolrich; | arxiv-cs.LG | 2025-10-20 |
| 629 | Visual Interestingness Decoded: How GPT-4o Mirrors Human Interests Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The rise of Large Multimodal Models (LMMs) trained on large-scale visual and textual data has demonstrated impressive capabilities. We explore these models’ potential to understand to what extent the concepts of visual interestingness are captured and examine the alignment between human assessments and GPT-4o’s, a leading LMM, predictions through comparative analysis. |
Fitim Abdullahu; Helmut Grabner; | iccv | 2025-10-20 |
| 630 | CARP: Visuomotor Policy Learning Via Coarse-to-Fine Autoregressive Prediction IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we introduce **C**oarse-to-Fine **A**uto**R**egressive **P**olicy (**CARP**), a novel paradigm for visuomotor policy learning that redefines the autoregressive action generation process as a coarse-to-fine, next-scale approach. |
ZHEFEI GONG et. al. | iccv | 2025-10-20 |
| 631 | Can Transformer Memory Be Corrupted? Investigating Cache-Side Vulnerabilities in Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper introduces Malicious TokenInjection (MTI), a modular framework that systematically perturbs cached keyvectors at selected layers and timesteps through controlled magnitude andfrequency, using additive Gaussian noise, zeroing, and orthogonal rotations. |
Elias Hossain; Swayamjit Saha; Somshubhra Roy; Ravi Prasad; | arxiv-cs.CR | 2025-10-19 |
| 632 | AI-Generated Text Detection in Low-Resource Languages: A Case Study on Urdu Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This challenge becomes even moreserious for languages like Urdu, where there are very few tools available todetect AI-generated text. To address this gap, we propose a novel AI-generatedtext detection framework tailored for the Urdu language. |
Muhammad Ammar; Hadiya Murad Hadi; Usman Majeed Butt; | arxiv-cs.CL | 2025-10-18 |
| 633 | Cultural Prompting Improves The Empathy and Cultural Responsiveness of GPT-Generated Therapy Responses Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Large Language Model (LLM)-based conversational agents offer promising solutions for mental health support, but lack cultural responsiveness for diverse populations. |
SERENA JINCHEN XIE et. al. | arxiv-cs.HC | 2025-10-18 |
| 634 | Automated Review of Spine Surgery Operative Reports with Large Language Models: A Pilot Study of GPT Reasoning Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save |
RUSHMIN KHAZANCHI et. al. | Journal of Clinical Neuroscience | 2025-10-18 |
| 635 | Fine-Tuning Large Language Models for Effective Nutrition Support in Residential Aged Care: A Domain Expertise Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Future work includes further optimisation of prediction performance and integration with clinical workflows to support early intervention. |
MOHAMMAD ALKHALAF et. al. | Healthcare | 2025-10-17 |
| 636 | Analyzing Student Mental Health with RoBERTa-Large: A Sentiment Analysis and Data Analytics Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this study, our primary objective was to investigate the mental health of students by conducting sentiment analysis using advanced deep learning models. |
Hikmat Ullah Khan; Anam Naz; Fawaz Khaled Alarfaj; Naif Almusallam; | Frontiers in Big Data | 2025-10-17 |
| 637 | Mixture of Experts Approaches in Dense Retrieval Tasks Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we propose a more efficient design, whichintroduces a single MoE block (SB-MoE) after the final Transformer layer. |
Effrosyni Sokli; Pranav Kasela; Georgios Peikos; Gabriella Pasi; | arxiv-cs.IR | 2025-10-17 |
| 638 | Reasoning-based LLMs Surpass Average Human Performance on Medical Social Skills Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Domain-specific analysis revealed that despite having equal overall scores, GPT-4o and Gemini 1.5 Pro -developed by two different companies- had varying strengths. |
Khalid Ibraheem Alohali; Laura Asaad Almusaeeb; Abdulaziz Abdulrahman Almubarak; Ahmad Ibraheem Alohali; Ruaim Abdullah Muaygil; | Scientific Reports | 2025-10-17 |
| 639 | PUMA: Secure Inference of LLaMA-7B in Five Minutes IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: To this end, we propose an MPC framework Puma to enable secure and efficient Transformer model inference. |
YE DONG et. al. | Security and Safety | 2025-10-16 |
| 640 | First Attentions Last: Better Exploiting First Attentions for Efficient Transformer Training Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Motivated by the observations,we propose FAL (First Attentions Last), an efficient transformer architecturethat redirects the first MHA output to the MLP inputs of the following layers,eliminating the per-block MHA-MLP connections. |
GYUDONG KIM et. al. | arxiv-cs.LG | 2025-10-16 |
| 641 | A Novel GPT-Based Framework for Anomaly Detection in System Logs Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Identification of anomalous events within system logs constitutes a pivotalelement within the frame- work of cybersecurity defense strategies. However,this process faces numerous … |
Zeng Zhang; Wenjie Yin; Xiaoqi Li; | arxiv-cs.CR | 2025-10-16 |
| 642 | A Free Lunch in LLM Compression: Revisiting Retraining After Pruning Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work,we study the key design choices when reconstructing or retraining the remainingweights after pruning. |
Moritz Wagner; Christophe Roux; Max Zimmer; Sebastian Pokutta; | arxiv-cs.LG | 2025-10-16 |
| 643 | AI-Powered Early Diagnosis of Mental Health Disorders from Real-World Clinical Conversations Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this study, we evaluate the effectiveness ofmachine learning models for mental health screening using a unique dataset of553 real-world, semistructured interviews, each paried with ground-truthdiagnoses for major depressive episodes (MDE), anxiety disorders, and PTSD. |
Jianfeng Zhu; Julina Maharjan; Xinyu Li; Karin G. Coifman; Ruoming Jin; | arxiv-cs.CL | 2025-10-16 |
| 644 | Deep Learning Algorithm Based Smart Tourism: Addressing Role, Challenges and Research Gaps in Exploration and Narration Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This research explores how Artificial Intelligence can transform the tourism industry through classification techniques and Natural Language Processing models. |
Dattatray Sadashiv Arade; Shriram Dagadu Raut; | International Journal of Computer Science and Mobile … | 2025-10-16 |
| 645 | Leveraging Large Language Models to Generate Multiple-Choice Questions for Ophthalmology Education Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Design, Setting, and Participants This survey study, conducted from September 2024 to April 2025, assesses LLM performance in generating MCQs based on the American Academy of Ophthalmology (AAO) Basic and Clinical Science Course ( BCSC ) compared with a committee of human experts. |
SHAHRZAD GHOLAMI et. al. | JAMA Ophthalmology | 2025-10-16 |
| 646 | How Deep Is Representational Bias in LLMs? The Cases of Caste and Religion Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We find that GPT-4 responses consistently overrepresent culturally dominant groups far beyond their statistical representation, despite prompts intended to encourage representational diversity. |
AGRIMA SETH et. al. | Proceedings of the AAAI/ACM Conference on AI, Ethics, and … | 2025-10-15 |
| 647 | Assessing Web Search Credibility and Response Groundedness in Chat Assistants Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we introduce a novel methodology forevaluating assistants’ web search behavior, focusing on source credibility andthe groundedness of responses with respect to cited sources. |
Ivan Vykopal; Matúš Pikuliak; Simon Ostermann; Marián Šimko; | arxiv-cs.CL | 2025-10-15 |
| 648 | Evaluating Large Language Models for Sentiment Analysis and Hesitancy Analysis on Vaccine Posts From Social Media: Qualitative Study Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Objective This study aims to evaluate the performance of various LLMs in sentiment analysis and hesitancy detection related to vaccine discussions on social media and identify the most efficient, accurate, and cost-effective model for detecting vaccine-related public sentiment and hesitancy trends. |
AUGUSTINE ANNAN et. al. | JMIR Formative Research | 2025-10-15 |
| 649 | IAD-GPT: Advancing Visual Knowledge in Multimodal Large Language Model for Industrial Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, weexplore the combination of rich text semantics with both image-level andpixel-level information from images and propose IAD-GPT, a novel paradigm basedon MLLMs for IAD. |
ZEWEN LI et. al. | arxiv-cs.CV | 2025-10-15 |
| 650 | David Vs. Goliath: A Comparative Study of Different-sized LLMs for Code Generation in The Domain of Automotive Scenario Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Weintroduce NL2Scenic, an open dataset and framework with 146 NL/Scenic pairs, adifficulty-stratified 30-case test split, an Example Retriever, and 14prompting variants (ZS, FS, CoT, SP, MoT). We evaluate 13 models: fourproprietary (GPT-4o, GPT-5, Claude-Sonnet-4, Gemini-2.5-pro) and nineopen-source code models (Qwen2.5Coder 0.5B-32B; CodeLlama 7B/13B/34B), usingtext metrics (BLEU, ChrF, EDIT-SIM, CrystalBLEU) and execution metrics(compilation and generation), and compare them with an expert study (n=11). |
PHILIPP BAUERFEIND et. al. | arxiv-cs.SE | 2025-10-15 |
| 651 | Modelado Semántico De Emergencias Del ECU 911 Con NLP Y Ontologías Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study proposes a novel hybrid framework for knowledge representation in emergencies, integrating Natural Language Processing (NLP), OWL ontologies, and SWRL rules to process unstructured data from Ecuador’s Integrated Security Service (ECU 911). |
Danny Leonardo Paltin Chica; Juan Diego Mejía Mendieta; Marcos Orellana; Jorge Luis Zambrano-Martinez; | Revista Tecnológica – ESPOL | 2025-10-15 |
| 652 | Noise-Adaptive Layerwise Learning Rates: Accelerating Geometry-Aware Optimization for Deep Neural Network Training Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we introduce a noise-adaptive layerwise learning rate schemeon top of geometry-aware optimization algorithms and substantially accelerateDNN training compared to methods that use fixed learning rates within eachgroup. |
Jie Hao; Xiaochuan Gong; Jie Xu; Zhengdao Wang; Mingrui Liu; | arxiv-cs.LG | 2025-10-15 |
| 653 | NEUROXL-CRFNET: A HYBRID TRANSFORMER–GRAPH FRAMEWORK FOR AUTOMATED HEPATOCELLULAR CARCINOMA HISTOPATHOLOGY CLASSIFICATION Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this research work, a novel deep learning-based framework for automated hepatocellular carcinoma (HCC) detection from histopathological images is introduced. |
International Journal of Applied Mathematics | 2025-10-15 | |
| 654 | DETECTION OF MACHINE-GENERATED TEXT BY INTEGRATING ROBERTA EMBEDDINGS WITH TOPOLOGICAL FEATURES Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The pervasive presence of highly advanced language models and hence machine- generated content has heightened concerns surrounding the spread of misinformation and the proliferation of deceptive and plagiarized content. To address this pressing challenge, an innovative solution exists in harnessing the combined power of the RoBERTa (Robustly Optimized BERT Approach) model and TDA (Topological Data Analysis) features to develop a model capable of discerning between human and machine-generated text effectively. |
Rejimoan R,; | International Journal of Applied Mathematics | 2025-10-15 |
| 655 | Timelygpt: Extrapolatable Transformer Pre-training for Long-term Time-series Forecasting in Healthcare Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Methods In this study, we present Timely Generative Pre-trained Transformer (TimelyGPT). |
ZIYANG SONG et. al. | Health Information Science and Systems | 2025-10-14 |
| 656 | Toward LLM-Supported Automated Assessment of Critical Thinking Subskills Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We developed a coding rubric based on an established skills progressionand completed human coding for a corpus of student essays. |
MARISA C. PECZUH et. al. | arxiv-cs.CY | 2025-10-14 |
| 657 | Efficient Toxicity Detection in Gaming Chats: A Comparative Study of Embeddings, Fine-Tuned Transformers and LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents a comprehensive comparative analysis of Natural Language Processing (NLP) methods for automated toxicity detection in online gaming chats. |
Yehor Tereshchenko; Mika K Hämäläinen; | Journal of Data Mining & Digital Humanities | 2025-10-14 |
| 658 | Attribution Quality in AI-Generated Content:Benchmarking Style Embeddings and LLM Judges Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To support reproducibility we provide code onGitHub and derived data on Hugging Face under the MIT license. |
Misam Abbas; | arxiv-cs.CL | 2025-10-14 |
| 659 | Efficient Adaptive Transformer: An Empirical Study and Reproducible Framework Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The Efficient Adaptive Transformer (EAT) framework unifies three adaptiveefficiency techniques – progressive token pruning, sparse attention, anddynamic early exiting – into a … |
Jan Miller; | arxiv-cs.CL | 2025-10-14 |
| 660 | Refining Hybrid Genetic Search for CVRP Via Reinforcement Learning-Finetuned LLM Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose RFTHGS, a novel Reinforcement learning (RL) framework forFine-Tuning a small LLM to generate high-performance crossover operators forthe Hybrid Genetic Search (HGS) solver, applied to the Capacitated VRP (CVRP). |
Rongjie Zhu; Cong Zhang; Zhiguang Cao; | arxiv-cs.LG | 2025-10-13 |
| 661 | Fairness Metric Design Exploration in Multi-Domain Moral Sentiment Classification Using Transformer-Based Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Per-label analysis reveals fairnessviolations hidden by overall scores; notably, the authority label exhibitsDemographic Parity Differences of 0.22-0.23 and Equalized Odds Differences of0.40-0.41. To address this gap, we introduce the Moral Fairness Consistency(MFC) metric, which quantifies the cross-domain stability of moral foundationdetection. |
Battemuulen Naranbat; Seyed Sahand Mohammadi Ziabari; Yousuf Nasser Al Husaini; Ali Mohammed Mansoor Alsahag; | arxiv-cs.CL | 2025-10-13 |
| 662 | GPT-4o and The Quest for Machine Learning Interpretability in ICU Risk of Death Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Methods A hybrid mechanistic/data-driven modeling framework is presented for developing an ICU risk of death prediction model for mechanically ventilated patients. |
Moein E. Samadi; Kateryna Nikulina; Sebastian Johannes Fritsch; Andreas Schuppert; | BMC Medical Informatics and Decision Making | 2025-10-13 |
| 663 | DocReward: A Document Reward Model for Structuring and Stylizing Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We construct a multi-domain dataset DocPair of 117K paireddocuments, covering 32 domains and 267 document types, each including a high-and low-professionalism document with identical content but different structureand style. |
JUNPENG LIU et. al. | arxiv-cs.CV | 2025-10-13 |
| 664 | When Does Supervised Training Pay Off? The Hidden Economics of Object Detection in The Era of Vision-Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We provide decision frameworks showingthat optimal architecture choice depends on inference volume, categorystability, budget, and accuracy requirements. |
Samer Al-Hamadani; | arxiv-cs.CV | 2025-10-13 |
| 665 | BERT-Based Sentiment Analysis of Turkish E-Commerce Reviews: Star Ratings Versus Text Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study examines sentiment analysis in Turkish e-commerce product reviews by comparing two distinct approaches: classification based on star ratings and textual sentiment using a BERT-based model. |
Ayşe Öcal; | Sakarya University Journal of Computer and Information … | 2025-10-13 |
| 666 | Enhancing The Accuracy of GPT Models in Kidney Stone Diagnosis A Comparison and Optimization of GPT 3.5 and GPT 4.0 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: As artificial intelligence advances, Large Language Models (LLMs) have shown tremendous potential in medical diagnosis and treatment, yet existing research has not extensively explored their application in kidney stones. |
Haoyang Zeng; | Journal of Artificial Intelligence & Robotics | 2025-10-13 |
| 667 | Using Large Language Models to Analyze Interviews for Driver Psychological Assessment: A Performance Comparison of ChatGPT and Google-Gemini Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study examines the application of large language models (LLMs) in analyzing subjective driver perceptions during tunnel driving simulations, comparing the effectiveness of questionnaires and interviews. |
RUIFEN SUN et. al. | Symmetry | 2025-10-13 |
| 668 | The Hidden DNA of LLM-Generated JavaScript: Structural Patterns Enable High-Accuracy Authorship Attribution Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we present the first large-scale study exploring whetherJavaScript code generated by Large Language Models (LLMs) can reveal whichmodel produced it, enabling reliable authorship attribution and modelfingerprinting. |
Norbert Tihanyi; Bilel Cherif; Richard A. Dubniczky; Mohamed Amine Ferrag; Tamás Bisztray; | arxiv-cs.CR | 2025-10-12 |
| 669 | HiligayNER: A Baseline Named Entity Recognition Model for Hiligaynon Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study introduces HiligayNER, thefirst publicly available baseline model for the task of Named EntityRecognition (NER) in Hiligaynon. |
JAMES ALD TEVES et. al. | arxiv-cs.CL | 2025-10-12 |
| 670 | Safeguarding Efficacy in Large Language Models: Evaluating Resistance to Human-Written and Algorithmic Adversarial Prompts Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents a systematic security assessment of four prominent LargeLanguage Models (LLMs) against diverse adversarial attack vectors. |
Tiarnaigh Downey-Webb; Olamide Jogunola; Oluwaseun Ajao; | arxiv-cs.CR | 2025-10-12 |
| 671 | The AI Annotator: Large Language Models’ Potential in Scoring Sustainability Reports Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: To explore the potential of Large Language Models (LLMs) as AI Annotators in the domain of sustainability reporting, this study establishes a systematic evaluation methodology. We … |
Yue Wu; Peng Hu; Derek D. Wang; | Syst. | 2025-10-11 |
| 672 | AI-enhanced Flexible ECG Patch for Accurate Heart Disease Diagnosis, Optimal Wear Positioning, and Interactive Medical Consultation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Our work enhances accessibility to cardiac care, promotes early detection, and reduces the burden on healthcare systems. |
XIAOJIANG HUANG et. al. | National Science Review | 2025-10-11 |
| 673 | Lightweight Baselines for Medical Abstract Classification: DistilBERT with Cross-Entropy As A Strong Default Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The research evaluates lightweight medical abstract classification methods toestablish their maximum performance capabilities under financial budgetrestrictions. |
JIAQI LIU et. al. | arxiv-cs.CL | 2025-10-11 |
| 674 | Deliberative Dynamics and Value Alignment in LLM Debates Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Most evaluations study this sociotechnical alignmentthrough single-turn prompts, but it is unclear if these findings extend tomulti-turn settings where values emerge through dialogue, revision, andconsensus. We address this gap using LLM debate to examine deliberativedynamics and value alignment in multi-turn settings by prompting subsets ofthree models (GPT-4.1, Claude 3.7 Sonnet, and Gemini 2.0 Flash) to collectivelyassign blame in 1,000 everyday dilemmas from Reddit’s Am I the Assholecommunity. |
Pratik S. Sachdeva; Tom van Nuenen; | arxiv-cs.AI | 2025-10-11 |
| 675 | GPT-based Lifelong Learning and ANFIS-driven Reply Memory Ratio Prediction for Aspect-based Sentiment Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Save |
HUANG HUANG et. al. | Complex & Intelligent Systems | 2025-10-10 |
| 676 | Weight Initialization and Variance Dynamics in Deep Neural Networks and Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper offers a theory-grounded and empiricallyvalidated study across two regimes: compact ReLU multilayer perceptrons andGPT-2-style transformers. |
Yankun Han; | arxiv-cs.LG | 2025-10-10 |
| 677 | Domain-Adapted Pre-trained Language Models for Implicit Information Extraction in Crash Narratives Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To bridge domain gaps, we apply fine-tuning techniques to injecttask-specific knowledge to LLMs with Low-Rank Adaption (LoRA) and BERT.Experiments on the authoritative real-world dataset Crash InvestigationSampling System (CISS) demonstrate that our fine-tuned compact modelsoutperform strong closed LLMs, such as GPT-4o, while requiring only minimaltraining resources. |
XIXI WANG et. al. | arxiv-cs.CL | 2025-10-10 |
| 678 | Hallucination Filtering in Radiology Vision-Language Models Using Discrete Semantic Entropy Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To determine whether using discrete semantic entropy (DSE) to rejectquestions likely to generate hallucinations can improve the accuracy ofblack-box vision-language models (VLMs) in radiologic image based visualquestion answering (VQA). |
PATRICK WIENHOLT et. al. | arxiv-cs.CV | 2025-10-10 |
| 679 | Learning Bug Context for PyTorch-to-JAX Translation with LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present T2J, a prompt-augmentation framework that strengthensLLM-based PyTorch to JAX translation. |
Hung Phan; Son Le Vu; Ali Jannesari; | arxiv-cs.LG | 2025-10-10 |
| 680 | Exploring Cross-Lingual Knowledge Transfer Via Transliteration-Based MLM Fine-Tuning for Critically Low-resource Chakma Language Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we introduce a novel corpusof contextually coherent Bangla-transliterated Chakma, curated from Chakmaliterature, and validated by native speakers. |
ADITY KHISA et. al. | arxiv-cs.CL | 2025-10-10 |
| 681 | A SNAPpy Use of Large Language Models: Using Large Language Models to Classify Treatment Plans in Pediatric Acute Otitis Media Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Methods A retrospective cross-sectional study analyzed pediatric AOM encounters. |
JESSICA J POURIAN et. al. | Journal of the American Medical Informatics Association | 2025-10-10 |
| 682 | ACE: Attribution-Controlled Knowledge Editing for Multi-hop Factual Recall Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We discover that during multi hop reasoning, implicitsubjects function as query neurons, which sequentially activate correspondingvalue neurons across transformer layers to accumulate information toward thefinal answer, a dynamic prior KE work has overlooked. Guided by this insight,we propose ACE: Attribution-Controlled Knowledge Editing for Multi-hop FactualRecall, a framework that leverages neuron-level attribution to identify andedit these critical query-value (Q-V) pathways. |
JIAYU YANG et. al. | arxiv-cs.CL | 2025-10-09 |
| 683 | Sentiment-Enhanced Cyberbullying Detection Models on Social Media Platforms Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study presents the first systematic comparison of sentiment-enhanced transformer models such as ALBERT, DeBERTa, ELECTRA, HateBERT, and DeepSeek-coder-1.3b-base, fine-tuned for cyberbullying detection across Twitter (currently X), IMDB, and Amazon. |
ADAMU PHILIPO et. al. | ACM Transactions on the Web | 2025-10-09 |
| 684 | Detecting Legend Items on Historical Maps Using GPT-4o with In-Context Learning Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Historical map legends are critical for interpreting cartographic symbols.However, their inconsistent layouts and unstructured formats make automaticextraction challenging. Prior … |
Sofia Kirsanova; Yao-Yi Chiang; Weiwei Duan; | arxiv-cs.CV | 2025-10-09 |
| 685 | Single Layer Tiny Co$^4$ Outpaces GPT-2 and GPT-BERT Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We show that a tiny Co$^4$ machine(Adeel,2025) with a single layer, twoheads, and 8M parameters, operating at an approximate cost of $O(N)$ (where $N$is the number of input tokens), outpaces the BabyLM Challenge baselines GPT-2(124M, 12 layers, $O(N^2))$ and GPT-BERT (30M, 12 layers, $O(N^2))$ in just twoepochs, while both are trained for ten. |
Noor Ul Zain; Mohsin Raza; Ahsan Adeel; | arxiv-cs.CL | 2025-10-09 |
| 686 | Large Language Models: A Paradigm Shift for Dementia Diagnosis and Care Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This review explores the prospect of LLMs transforming dementia management and addresses the ethical and practical considerations involved. |
JUDITH ROSE HARRISON et. al. | British Journal of Hospital Medicine | 2025-10-09 |
| 687 | Exploring AI’s Potential in Papilledema Diagnosis to Support Dermatological Treatment Decisions in Rural Healthcare Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Objective: The primary objective of this study was to explore the diagnostic capability of ChatGPT-4o, a general large language model with multimodal input, in identifying papilledema from fundus photographs. |
JONATHAN SHAPIRO et. al. | Diagnostics | 2025-10-09 |
| 688 | FAR-AM: A Hybrid Attention Framework for Fire Cause Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, existing deep learning models often struggle with the unique challenges these documents present—namely their extreme length, high semantic noise, and fragmented causal information. To overcome these limitations, we propose the Fire Accident Reports Attention Mechanism (FAR-AM), a novel hybrid deep learning framework. |
Heng Peng; Kun Zhu; | PLOS One | 2025-10-09 |
| 689 | GPT-5 Model Corrected GPT-4V’s Chart Reading Errors, Not Prompting Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present a quantitative evaluation to understand the effect of zero-shotlarge-language model (LLMs) and prompting uses on chart reading tasks. |
Kaichun Yang; Jian Chen; | arxiv-cs.HC | 2025-10-08 |
| 690 | On The Effectiveness of Limited-data Large Language Model Fine-tuning for Arabic Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents an investigation into fine-tuning large language models (LLMs) for Arabic natural language processing (NLP) tasks. |
Mohamed Alkaoud; | PLOS One | 2025-10-08 |
| 691 | Cancer Diagnosis Categorization in Electronic Health Records Using Large Language Models and BioBERT: Model Performance Evaluation Study Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Electronic health records contain inconsistently structured or free-textdata, requiring efficient preprocessing to enable predictive health caremodels. Although artificial … |
SOHEIL HASHTARKHANI et. al. | arxiv-cs.CL | 2025-10-08 |
| 692 | Biasless Language Models Learn Unnaturally: How LLMs Fail to Distinguish The Possible from The Impossible Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This question is taken bymany to bear on whether LLMs and humans share the same innate learning biases.Previous work has attempted to answer it in the positive by comparing LLMlearning curves on existing language datasets and on impossible datasetsderived from them via various perturbation functions. Using the samemethodology, we examine this claim on a wider set of languages and impossibleperturbations. |
Imry Ziv; Nur Lan; Emmanuel Chemla; Roni Katzir; | arxiv-cs.CL | 2025-10-08 |
| 693 | RETRIEVAL AUGMENTED NEURAL ADAPTERS FOR DOMAIN SPECIFIC CUSTOMIZATION OF LARGE LANGUAGE MODELS Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper introduces Retrieval‑Augmented Neural Adapters (RANA) a scalable framework that augments a frozen LLM with a lightweight neural adapter and a retrieval module. |
Abha Kiran Rajpoot; | International Journal of Applied Mathematics | 2025-10-08 |
| 694 | Judgments of Learning Distinguish Humans from Large Language Models in Predicting Memory Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Here, we introduce a cross-agent prediction model to assess whether ChatGPT-based LLMs align with human judgments of learning (JOL), a metacognitive measure where individuals predict their own future memory performance. |
Markus Huff; Elanur Ulakci; | Scientific Reports | 2025-10-07 |
| 695 | Evaluating The Impact of Stimulus Quality in Investigations of LLM Language Performance Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper investigates the hypothesis thatcharacteristics of the stimuli used in recent studies, including lexicalambiguities and structural complexities, may confound model performance. |
Timothy Pistotti; Jason Brown; Michael Witbrock; | arxiv-cs.CL | 2025-10-07 |
| 696 | Vision Transformer for Transient Noise Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We aim to classify glitches in LIGO data into 22 existingclasses from the first run plus 2 additional noise classes from O3a using theVision Transformer (ViT) model. |
Divyansh Srivastava; Andrzej Niedzielski; | arxiv-cs.CV | 2025-10-06 |
| 697 | Audit-style Framework for Evaluating Bias in Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose an evaluation framework for assessing whether a system exhibits biased behavior. |
Peter Baldwin; | Frontiers in Education | 2025-10-06 |
| 698 | Has AI Surpassed Humans in Creative Idea Generation? A Meta-Analysis Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Has AI surpassed humans in creative idea generation? This question has gained traction as generative AI (GenAI) has become widely used to support creativity. To evaluate this, we … |
Alwin de Rooij; M. M. Biskjaer; | Proceedings of the 36th Annual Conference of the European … | 2025-10-06 |
| 699 | A Supplement, Not A Substitute: Accuracy and Completeness of ChatGPT Responses for Common Elbow Pathology Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The present study comparatively assessed both ChatGPT 3.5 and GPT-4 responses to frequently asked questions on common elbow pathologies, scoring for accuracy and completeness. |
BENJAMIN FIEDLER et. al. | Shoulder & Elbow | 2025-10-06 |
| 700 | AgentTypo: Adaptive Typographic Prompt Injection Attacks Against Black-box Multimodal Agents Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce AgentTypo, ablack-box red-teaming framework that mounts adaptive typographic promptinjection by embedding optimized text into webpage images. |
Yanjie Li; Yiming Cao; Dong Wang; Bin Xiao; | arxiv-cs.CR | 2025-10-05 |
| 701 | Fine-Tuning Large Language Models with QLoRA for Offensive Language Detection in Roman Urdu-English Code-Mixed Text Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Inthis work, we propose a QLoRA based fine tuning framework to improve offensivelanguage detection in Roman Urdu-English text. |
NISAR HUSSAIN et. al. | arxiv-cs.CL | 2025-10-04 |
| 702 | Perbandingan Bidirectional Encoder Representations from Transformers (BERT) Language Model Pada Deteksi Emosi Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Informasi Tekstual menjadi salah satu cara untuk deteksi emosi. Namun, ekstraksi emosi menjadi tantangan tersendiri dikarenakan makna implisit dan eksplisit yang terkandung dalam … |
Dwi Hosanna Bangkalang; Nina Setiyawati; | Jurnal Pendidikan dan Teknologi Indonesia | 2025-10-04 |
| 703 | Annotate Rhetorical Relations with INCEpTION: A Comparison with Automatic Approaches Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This research explores the annotation of rhetorical relations in discourseusing the INCEpTION tool and compares manual annotation with automaticapproaches based on large language models. |
Mehedi Hasan Emon; | arxiv-cs.CL | 2025-10-04 |
| 704 | LLM, Reporting In! Medical Information Extraction Across Prompting, Fine-tuning and Post-correction Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: For NER, we propose three approaches combining largelanguage models (LLMs), annotation guidelines, synthetic data, andpost-processing: (1) in-context learning (ICL) with GPT-4.1, incorporatingautomatic selection of 10 examples and a summary of the annotation guidelinesinto the prompt, (2) the universal NER system GLiNER, fine-tuned on a syntheticcorpus and then verified by an LLM in post-processing, and (3) the open LLMLLaMA-3.1-8B-Instruct, fine-tuned on the same synthetic corpus. |
IKRAM BELMADANI et. al. | arxiv-cs.CL | 2025-10-03 |
| 705 | Detecting LLM-Generated Spam Reviews By Integrating Language Model Embeddings and Graph Neural Network Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To address thisthreat, we propose FraudSquad, a hybrid detection model that integrates textembeddings from a pre-trained language model with a gated graph transformer forspam node classification. |
XIN LIU et. al. | arxiv-cs.CL | 2025-10-02 |
| 706 | Hierarchical Semantic Retrieval with Cobweb Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We evaluate our approaches on MS MARCO and QQPwith encoder (e.g., BERT/T5) and decoder (GPT-2) representations. |
Anant Gupta; Karthik Singaravadivelan; Zekun Wang; | arxiv-cs.CL | 2025-10-02 |
| 707 | Enhanced Arabic-language Cyberbullying Detection: Deep Embedding and Transformer (BERT) Approaches Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper aims to enhance theeffectiveness of methods for detecting cyberbullying in Arabic-languagecontent. |
Ebtesam Jaber Aljohani; Wael M. S. Yafoo; | arxiv-cs.CL | 2025-10-02 |
| 708 | A Locally Executable AI System for Improving Preoperative Patient Communication: A Multi-Domain Clinical Evaluation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present LENOHA (Low Energy, No Hallucination, LeaveNo One Behind Architecture), a safety-first, local-first system that routesinputs with a high-precision sentence-transformer classifier and returnsverbatim answers from a clinician-curated FAQ for clinical queries, eliminatingfree-text generation in the clinical path. |
MOTOKI SATO et. al. | arxiv-cs.AI | 2025-10-02 |
| 709 | ENLighten: Lighten The Transformer, Enable Efficient Optical Acceleration Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To address thesechallenges, we introduce a hardware–software co-design framework. |
HANQING ZHU et. al. | arxiv-cs.ET | 2025-10-02 |
| 710 | C-Transformer: An Energy-Efficient Homogeneous DNN-Transformer/SNN-Transformer Processor for Large Language Models Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: In this article, we propose a new language model processor named the C-Transformer to address the external memory bottleneck of language models. It consists of three key … |
SANGYEOB KIM et. al. | IEEE Journal of Solid-State Circuits | 2025-10-01 |
| 711 | Hybrid Dialogue State Tracking for Persian Chatbots: A Language Model-Based Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study proposes a hybrid DST modelthat utilizes rule-based methods along with language models, including BERT forslot filling and intent detection, XGBoost for intent validation, GPT for DST,and online agents for real-time answer generation. |
Samin Mahdipour Aghabagher; Saeedeh Momtazi; | arxiv-cs.CL | 2025-10-01 |
| 712 | MGGPT: A Multi-Graph GPT-enhanced Framework for Dynamic Fraud Detection in Cryptocurrency Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Save |
Ansu Badjie; Grace Mupoyi Ntuala; Qi Xia; Jianbin Gao; Hu Xia; | Comput. Networks | 2025-10-01 |
| 713 | TDR-Transformer: A Transformer Neural Network Model to Determine Soil Relative Permittivity Variations Along A Time Domain Reflectometry Sensor Waveguide Related Papers Related Patents Related Grants Related Venues Related Experts View Save |
ZHUANGJI WANG et. al. | Comput. Electron. Agric. | 2025-10-01 |
| 714 | EGPT-SPE: Story Point Effort Estimation Using Improved GPT-2 By Removing Inefficient Attention Heads Related Papers Related Patents Related Grants Related Venues Related Experts View Save |
AMNA SHAHID CHEEMAA et. al. | Applied Intelligence | 2025-10-01 |
| 715 | CUET_Zenith at LLMs4OL 2025 Task C: Hybrid Embedding-LLM Architectures for Taxonomy Discovery Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Taxonomy discovery, the identification of hierarchical relationships within ontological structures, constitutes a foundational challenge in ontology learning. Our submission to … |
Rehenuma Ilman; Mehreen Rahman; Samia Rahman; | Open Conference Proceedings | 2025-10-01 |
| 716 | T-GreC at LLMs4OL 2025 Task B: A Report on Term-Typing Task of OBI Dataset Using LLM with K-Nearest Neighbors Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: This report presents an approach that combines large language models’ (LLMs) embedding with k-nearest neighbors (k-NN) for the term-typing task on the OBI (Ontology for Biomedical … |
Chavakan Yimmark; Teeradaj Racharak; | Open Conference Proceedings | 2025-10-01 |
| 717 | A Systematic Comparison of Large Language Models for Automated Assignment Assessment in Programming Education: Exploring The Importance of Architecture and Vendor Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study presents the first large-scale, side-by-side comparison ofcontemporary Large Language Models (LLMs) in the automated grading ofprogramming assignments. |
Marcin Jukiewicz; | arxiv-cs.CY | 2025-09-30 |
| 718 | Automated Alignment of Math Items to Content Standards in Large-Scale Assessments Using Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study evaluates three automatedparadigms for aligning items with four domain and nineteen skill labels. |
QINGSHU XU et. al. | arxiv-cs.CL | 2025-09-30 |
| 719 | Using GPT to Build A Project Management Assistant for Jira Environments Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work we present JiraGPT Next, a software that uses the GPT LargeLanguage Model to ease the process by which project managers deal with largeamounts of data. |
Joel Garcia-Escribano; Arkaitz Carbajo; Mikel Egaña Aranguren; Unai Lopez-Novoa; | arxiv-cs.SE | 2025-09-30 |
| 720 | Detecting Hope Across Languages: Multiclass Classification for Positive Online Discourse Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we presenta machine learning approach to multiclass hope speech detection across multiplelanguages, including English, Urdu, and Spanish. |
T. O. ABIOLA et. al. | arxiv-cs.CL | 2025-09-30 |
| 721 | LLM Based Sentiment Classification From Bangladesh E-Commerce Reviews Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The viability of usingtransformer-based BERT models and other LLMs for sentiment analysis fromBangladesh e commerce reviews is investigated in this paper. |
Sumaiya Tabassum; | arxiv-cs.CL | 2025-09-30 |
| 722 | Large Language Models Inference Engines Based on Spiking Neural Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we explore spiking neural networks(SNNs) to design transformer models. |
Adarsha Balaji; Sandeep Madireddy; Prasanna Balaprakash; | arxiv-cs.LG | 2025-09-30 |
| 723 | RadOnc-GPT: An Autonomous LLM Agent for Real-Time Patient Outcomes Labeling at Scale Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present RadOnc-GPT, an autonomouslarge language model (LLM)-based agent capable of independently retrievingpatient-specific information, iteratively assessing evidence, and returningstructured outcomes. |
JASON HOLMES et. al. | arxiv-cs.AI | 2025-09-29 |
| 724 | Federated Learning Meets LLMs: Feature Extraction From Heterogeneous Clients Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: A major obstacle, however, is the heterogeneityof tabular data across clients, where divergent schemas and incompatiblefeature spaces prevent straightforward aggregation. To address this challenge,we propose FedLLM-Align, a federated framework that leverages pre-trained largelanguage models (LLMs) as universal feature extractors. |
Abdelrhman Gaber; Hassan Abd-Eltawab; Youssif Abuzied; Muhammad ElMahdy; Tamer ElBatt; | arxiv-cs.LG | 2025-09-29 |
| 725 | An Agent-Based Framework for Automated Higher-Voice Harmony Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Our framework comprises four specialized agents: aMusic-Ingestion Agent for parsing and standardizing input musical scores; aChord-Knowledge Agent, powered by a Chord-Former (Transformer model), tointerpret and provide the constituent notes of complex chord symbols; aHarmony-Generation Agent, which utilizes a Harmony-GPT and a Rhythm-Net (RNN)to compose a melodically and rhythmically complementary harmony line; and anAudio-Production Agent that employs a GAN-based Symbolic-to-Audio Synthesizerto render the final symbolic output into high-fidelity audio. |
Nia D’Souza Ganapathy; Arul Selvamani Shaja; | arxiv-cs.SD | 2025-09-29 |
| 726 | Ensembling Multilingual Transformers for Robust Sentiment Analysis of Tweets Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this study, we presenta transformer ensemble model and a large language model (LLM) that employssentiment analysis of other languages. |
Meysam Shirdel Bilehsavar; Negin Mahmoudi; Mohammad Jalili Torkamani; Kiana Kiashemshaki; | arxiv-cs.CL | 2025-09-28 |
| 727 | Emission-GPT: A Domain-specific Language Model Agent for Knowledge Retrieval, Emission Inventory and Data Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To addressthis, we present Emission-GPT, a knowledge-enhanced large language model agenttailored for the atmospheric emissions domain. |
JIASHU YE et. al. | arxiv-cs.CL | 2025-09-28 |
| 728 | Quant Fever, Reasoning Blackholes, Schrodinger’s Compliance, and More: Probing GPT-OSS-20B Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: OpenAI’s GPT-OSS family provides open-weight language models with explicitchain-of-thought (CoT) reasoning and a Harmony prompt format. |
SHUYI LIN et. al. | arxiv-cs.AI | 2025-09-28 |
| 729 | FraudTransformer: Time-Aware GPT for Transaction Fraud Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Detecting payment fraud in real-world banking streams requires models thatcan exploit both the order of events and the irregular time gaps between them.We introduce FraudTransformer, a sequence model that augments a vanillaGPT-style architecture with (i) a dedicated time encoder that embeds eitherabsolute timestamps or inter-event values, and (ii) a learned positionalencoder that preserves relative order. |
GHOLAMALI AMINIAN et. al. | arxiv-cs.LG | 2025-09-28 |
| 730 | BeyondBench: Benchmark-Free Evaluation of Reasoning in Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In thispaper, we introduce BeyondBench, an evaluation framework that avoids thisproblem by using algorithmic problem generation. |
GAURAV SRIVASTAVA et. al. | arxiv-cs.CL | 2025-09-28 |
| 731 | WirelessMathLM: Teaching Mathematical Reasoning for LLMs in Wireless Communications with Reinforcement Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present WirelessMathLM, demonstrating that compact models(0.5B-7B parameters) can match or exceed much larger models throughdomain-specific reinforcement learning with verifiable rewards. |
XIN LI et. al. | arxiv-cs.LG | 2025-09-27 |
| 732 | The Impact of Role Design in In-Context Learning for Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We evaluate the models’performance across datasets, focusing on tasks like sentiment analysis, textclassification, question answering, and math reasoning. |
Hamidreza Rouzegar; Masoud Makrehchi; | arxiv-cs.CL | 2025-09-27 |
| 733 | Deep Learning for Oral Health: Benchmarking ViT, DeiT, BEiT, ConvNeXt, and Swin Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Objective: The aim of this study was to systematically evaluate and comparethe performance of five state-of-the-art transformer-based architectures -Vision Transformer (ViT), Data-efficient Image Transformer (DeiT), ConvNeXt,Swin Transformer, and Bidirectional Encoder Representation from ImageTransformers (BEiT) – for multi-class dental disease classification. |
Ajo Babu George; Sadhvik Bathini; Niranjana S R; | arxiv-cs.CV | 2025-09-27 |
| 734 | Multi-Agent Path Finding Via Offline RL and LLM Collaboration Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Decentralized reinforcement learning methods commonly encountertwo substantial difficulties: first, they often yield self-centered behaviorsamong agents, resulting in frequent collisions, and second, their reliance oncomplex communication modules leads to prolonged training times, sometimesspanning weeks. To address these challenges, we propose an efficientdecentralized planning framework based on the Decision Transformer (DT),uniquely leveraging offline reinforcement learning to substantially reducetraining durations from weeks to mere hours. |
Merve Atasever; Matthew Hong; Mihir Nitin Kulkarni; Qingpei Li; Jyotirmoy V. Deshmukh; | arxiv-cs.MA | 2025-09-26 |
| 735 | Large Language Models Management of Medications: Three Performance Analyses Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Purpose: Large language models (LLMs) have proven performance for certaindiagnostic tasks, however limited studies have evaluated their consistency inrecommending appropriate … |
KELLI HENRY et. al. | arxiv-cs.CL | 2025-09-26 |
| 736 | GPT-4 for Occlusion Order Recovery Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Occlusion remains a significant challenge for current vision models torobustly interpret complex and dense real-world images and scenes. To addressthis limitation and to enable accurate prediction of the occlusion orderrelationship between objects, we propose leveraging the advanced capability ofa pre-trained GPT-4 model to deduce the order. |
Kaziwa Saleh; Zhyar Rzgar K Rostam; Sándor Szénási; Zoltán Vámossy; | arxiv-cs.CV | 2025-09-26 |
| 737 | AI Kill Switch for Malicious Web-based LLM Agent Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, they also amplify the risks of malicious misuse cases such as unauthorized collection of personally identifiable information (PII), generation of socially divisive content, and even automated web hacking. To address these threats, we propose an AI Kill Switch technique that can immediately halt the operation of malicious web-based LLM agents. |
Sechan Lee; Sangdon Park; | arxiv-cs.CR | 2025-09-25 |
| 738 | Extracting Conceptual Knowledge to Locate Software Issues Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: While recent LLM-based andLLM-agent-based approaches improve accuracy, they struggle in large-scalerepositories due to concern tangling, where relevant logic is buried in largefunctions, and concern scattering, where related logic is dispersed acrossfiles. To address these challenges, we propose RepoLens, a novel approach thatabstracts and leverages conceptual knowledge from code repositories. |
YING WANG et. al. | arxiv-cs.SE | 2025-09-25 |
| 739 | In AI Sweet Harmony: Sociopragmatic Guardrail Bypasses and Evaluation-Awareness in OpenAI Gpt-oss-20b Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: On our grid, formalregisters in German and French are often leakier than matched English prompts.A Linux terminal role-play overrides a developer rule not to reveal contextin a majority of runs with a naive developer prompt, and we introduce anAI-assisted hardening method that reduces leakage to 0% in several user-promptvariants. |
Nils Durner; | arxiv-cs.CL | 2025-09-25 |
| 740 | An Improved Quantum Software Challenges Classification Approach Using Transfer Learning and Explainable AI Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We conducted studies to classifyquestions into various challenges. |
NEK DIL KHAN et. al. | arxiv-cs.SE | 2025-09-25 |
| 741 | Dual-Path Phishing Detection: Integrating Transformer-Based NLP with Structural URL Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we propose adual-path phishing detection framework that integrates transformer-basednatural language processing (NLP) with classical machine learning to jointlyanalyze email text and embedded URLs. |
Ibrahim Altan; Abdulla Bachir; Yousuf Parbhulkar; Abdul Muksith Rizvi; Moshiur Farazi; | arxiv-cs.CR | 2025-09-25 |
| 742 | SINAI at ERisk@CLEF 2025: Transformer-Based and Conversational Strategies for Depression Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper describes the participation of the SINAI-UJA team in theeRisk@CLEF 2025 lab. |
Alba Maria Marmol-Romero; Manuel Garcia-Vega; Miguel Angel Garcia-Cumbreras; Arturo Montejo-Raez; | arxiv-cs.CL | 2025-09-24 |
| 743 | SwasthLLM: A Unified Cross-Lingual, Multi-Task, and Meta-Learning Zero-Shot Framework for Medical Diagnosis Using Contrastive Representations Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper proposes SwasthLLM, a unified, zero-shot,cross-lingual, and multi-task learning framework for medical diagnosis thatoperates effectively across English, Hindi, and Bengali without requiringlanguage-specific fine-tuning. |
Ayan Sar; Pranav Singh Puri; Sumit Aich; Tanupriya Choudhury; Abhijit Kumar; | arxiv-cs.CL | 2025-09-24 |
| 744 | IA Aplicada Al Análisis Del Conflicto Irán-Israel: Mapeo De Discursos En YouTube Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study analyzes the digital representation of the Iran-Israelconflict that occurred in June 2025, based on 120,000 comments posted onYouTube. |
Alvaro Vallejo Ramírez; | arxiv-cs.SI | 2025-09-24 |
| 745 | Hierarchical Resolution Transformers: A Wavelet-Inspired Architecture for Multi-Scale Language Understanding Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We evaluated HRT on a diverse suite of benchmarks,including GLUE, SuperGLUE, Long Range Arena, and WikiText-103, and resultsdemonstrated that HRT outperforms standard transformer baselines by an averageof +3.8% on GLUE, +4.5% on SuperGLUE, and +6.1% on Long Range Arena, whilereducing memory usage by 42% and inference latency by 37% compared to BERT andGPT style models of similar parameter count. |
AYAN SAR et. al. | arxiv-cs.CL | 2025-09-24 |
| 746 | Multilingual Hope Speech Detection: A Comparative Study of Logistic Regression, MBERT, and XLM-RoBERTa with Active Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paperpresents a multilingual framework for hope speech detection using an activelearning approach and transformer-based models, including mBERT andXLM-RoBERTa. |
T. O. ABIOLA et. al. | arxiv-cs.CL | 2025-09-24 |
| 747 | GPT and Prejudice: A Sparse Approach to Understanding Learned Representations in Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we show that pairingLLMs with sparse autoencoders (SAEs) enables interpretation not only of modelbehavior but also of the deeper structures, themes, and biases embedded in thetraining data. |
Mariam Mahran; Katharina Simbeck; | arxiv-cs.CL | 2025-09-24 |
| 748 | Confidence Calibration in Large Language Model-Based Entity Matching Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This research aims to explore the intersection of Large Language Models andconfidence calibration in Entity Matching. |
IRIS KAMSTEEG et. al. | arxiv-cs.CL | 2025-09-23 |
| 749 | Human-Annotated NER Dataset for The Kyrgyz Language Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce KyrgyzNER, the first manually annotated named entity recognitiondataset for the Kyrgyz language. |
Timur Turatali; Anton Alekseev; Gulira Jumalieva; Gulnara Kabaeva; Sergey Nikolenko; | arxiv-cs.CL | 2025-09-23 |
| 750 | Thinking While Listening: Simple Test Time Scaling For Audio Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose a framework that enables neural models to think while listeningto everyday sounds, thereby enhancing audio classification performance.Motivated by recent advances in the reasoning capabilities of large languagemodels, we address two central questions: (i) how can thinking be incorporatedinto existing audio classification pipelines to enable reasoning in thecategory space and improve performance, and (ii) can a new architecture bedesigned from the ground up to support both thinking and test-time scaling? |
Prateek Verma; Mert Pilanci; | arxiv-cs.SD | 2025-09-23 |
| 751 | Systematic Comparative Analysis of Large Pretrained Language Models on Contextualized Medication Event Extraction Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this research a comparative analysis is doneamongst pre- trained attention based models namely Bert Base, BioBert, twovariations of Bio+Clinical Bert, RoBerta, and Clinical Long- former on taskrelated to Electronic Health Record (EHR) information extraction. |
Tariq Abdul-Quddoos; Xishuang Dong; Lijun Qian; | arxiv-cs.CL | 2025-09-23 |
| 752 | Gödel Test: Can Large Language Models Solve Easy Conjectures? Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose the G\odel Test: evaluating whethera model can produce correct proofs for very simple, previously unsolvedconjectures. |
Moran Feldman; Amin Karbasi; | arxiv-cs.AI | 2025-09-22 |
| 753 | Who Should Test The Requirement? A Comparative Study on Requirements Classification for Assigning Test Teams Using The Pre-Trained Models Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Analyzing software requirements is a complex task, particularly for projects with a large volume of requirements, and when conducted manually, this task is time-consuming and … |
Alay Nascimento; Flávia Oliveira; Leonardo Tiago; L. Chaves; | Brazilian Symposium on Software Engineering | 2025-09-22 |
| 754 | Enhancing Emotion Classification on The ISEAR Dataset Using Fine-tuning and Data Augmentation with Hybrid Transformer Models Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Emotion detection is a natural language processing task used in many applications, including customer support, human mental disorder identification, and analysis of social … |
UZAIR MUHAMMAD et. al. | PeerJ Comput. Sci. | 2025-09-22 |
| 755 | An N-Plus-1 GPT Agency for Critical Solution of Mechanical Engineering Analysis Problems Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce anN-Plus-1 GPT Agency for Initial (Low-Cost) Analysis of mechanical engineeringProblem Statements. |
Anthony Patera; Rohan Abeyaratne; | arxiv-cs.AI | 2025-09-22 |
| 756 | Solaria-GPT: A Tailored ChatGPT Tool for Usability Inspection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Usability defects in software systems result in challenges for users during their interactions with the software. To address these challenges, usability inspection is key for … |
Lennon Chaves; M. Lima; T. Conte; | Brazilian Symposium on Software Engineering | 2025-09-22 |
| 757 | Beyond Diagnosis: Evaluating Multimodal LLMs for Pathology Localization in Chest Radiographs Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Here, we systematically assess two general-purpose MLLMs(GPT-4 and GPT-5) and a domain-specific model (MedGemma) in their ability tolocalize pathologies on chest radiographs, using a prompting pipeline thatoverlays a spatial grid and elicits coordinate-based predictions. |
ADVAIT GOSAI et. al. | arxiv-cs.CV | 2025-09-22 |
| 758 | Evaluating Generative AI As An Educational Tool for Radiology Resident Report Drafting Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Methods: We analyzed 5,000 resident-attending report pairs from routinepractice at a multi-site U.S. health system. |
ANTONIO VERDONE et. al. | arxiv-cs.HC | 2025-09-22 |
| 759 | CLaC at DISRPT 2025: Hierarchical Adapters for Cross-Framework Multi-lingual Discourse Relation Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present our submission to Task 3 (Discourse Relation Classification) ofthe DISRPT 2025 shared task. |
Nawar Turk; Daniele Comitogianni; Leila Kosseim; | arxiv-cs.CL | 2025-09-20 |
| 760 | Assessing Classical Machine Learning and Transformer-based Approaches for Detecting AI-Generated Research Text Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We test and compare both classical (Logistic Regression armed withclassical Bag-of-Words, POS, and TF-IDF features) and transformer-based (BERTaugmented with N-grams, DistilBERT, BERT with a lightweight custom classifier,and LSTM-based N-gram models) ML detection techniques. |
Sharanya Parimanoharan; Ruwan D. Nawarathna; | arxiv-cs.CL | 2025-09-20 |
| 761 | Mental Multi-class Classification on Social Media: Benchmarking Transformer Architectures Against LSTM Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we present a large-scalecomparative study of state-of-the-art transformer versus Long Short-Term Memory(LSTM)-based models to classify mental health posts into exclusive categoriesof mental health conditions. |
Khalid Hasan; Jamil Saquer; Yifan Zhang; | arxiv-cs.CL | 2025-09-20 |
| 762 | Evaluation of Causal Reasoning for Large Language Models in Contextualized Clinical Scenarios of Laboratory Test Interpretation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study evaluates causal reasoning in large language models (LLMs) using99 clinically grounded laboratory test scenarios aligned with Pearl’s Ladder ofCausation: association, intervention, and counterfactual reasoning. |
BALU BHASURAN et. al. | arxiv-cs.AI | 2025-09-19 |
| 763 | Quality Assessment of GPT-3.5 and Gemini 1.0 Pro for SQL Syntax Related Papers Related Patents Related Grants Related Venues Related Experts View Save |
C. Roșca; Adrian Stancu; | Comput. Stand. Interfaces | |
| 764 | Interplay Between Belief Propagation and Transformer: Differential-Attention Message Passing Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents a novel decoderarchitecture that integrates classical belief propagation principles withtransformer designs. |
Chin Wa Lau; Xiang Shi; Ziyan Zheng; Haiwen Cao; Nian Guo; | arxiv-cs.IT | 2025-09-19 |
| 765 | EmoHeal: An End-to-End System for Personalized Therapeutic Music Retrieval from Fine-grained Emotions Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In thiswork, we present EmoHeal, an end-to-end system that delivers personalized,three-stage supportive narratives. |
Xinchen Wan; Jinhua Liang; Huan Zhang; | arxiv-cs.LG | 2025-09-19 |
| 766 | FairTune: A Bias-Aware Fine-Tuning Framework Towards Fair Heart Rate Prediction from PPG Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: While fine-tuning substantiallyreduces mean absolute error (up to 80%), it can simultaneously widen fairnessgaps, especially in larger models and under significant distributionalcharacteristics shifts. To address this, we introduce FairTune, a bias-awarefine-tuning framework in which we benchmark three mitigation strategies: classweighting based on inverse group frequency (IF), Group Distributionally RobustOptimization (GroupDRO), and adversarial debiasing (ADV). |
LOVELY YESWANTH PANCHUMARTHI et. al. | arxiv-cs.LG | 2025-09-19 |
| 767 | Leveraging LLMs for Automated Extraction and Structuring of Educational Concepts and Relationships Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Students must navigate large catalogs of courses and make appropriate enrollment decisions in many online learning environments. In this context, identifying key concepts and … |
TIANYUAN YANG et. al. | Mach. Learn. Knowl. Extr. | 2025-09-19 |
| 768 | Language Modeling with Learned Meta-Tokens Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: While modern Transformer-based language models (LMs) have achieved majorsuccess in multi-task generalization, they often struggle to capture long-rangedependencies within their context window. This work introduces a novel approachusing meta-tokens, special tokens injected during pre-training, along with adedicated meta-attention mechanism to guide LMs to use these tokens. |
Alok N. Shah; Khush Gupta; Keshav Ramji; Pratik Chaudhari; | arxiv-cs.CL | 2025-09-18 |
| 769 | Diffusion-Based Cross-Modal Feature Extraction for Multi-Label Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Multi-label classification has broad applications and depends on powerfulrepresentations capable of capturing multi-label interactions. We introduce\textit{Diff-Feat}, a simple but powerful framework that extracts intermediatefeatures from pre-trained diffusion-Transformer models for images and text, andfuses them for downstream tasks. |
Tian Lan; Yiming Zheng; Jianxin Yin; | arxiv-cs.CV | 2025-09-18 |
| 770 | HausaMovieReview: A Benchmark Dataset for Sentiment Analysis in Low-Resource African Language Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The dataset was meticulously annotated by threeindependent annotators, demonstrating a robust agreement with a Fleiss’ Kappascore of 0.85 between annotators. We used this dataset to conduct a comparativeanalysis of classical models (Logistic Regression, Decision Tree, K-NearestNeighbors) and fine-tuned transformer models (BERT and RoBERTa). |
ASIYA IBRAHIM ZANGA et. al. | arxiv-cs.CL | 2025-09-17 |
| 771 | Simulating Clinical AI Assistance Using Multimodal LLMs: A Case Study in Diabetic Retinopathy Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In actual collaboration, GPT-4oachieved strong results when guided by MedGemma’s descriptive outputs, evenwithout direct image access (AUROC up to 0.96). These findings suggest MLLMsmay improve DR screening pipelines and serve as scalable simulators forstudying clinical AI assistance across varying output configurations. |
Nadim Barakat; William Lotter; | arxiv-cs.AI | 2025-09-16 |
| 772 | Bhaasha, Bhasa, Zaban: A Survey for Low-Resourced Languages in South Asia — Current Stage and Challenges Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present advances and gaps across 3 essentialaspects: data, models, & tasks, such as available data sources, fine-tuningstrategies, & domain applications. |
Sampoorna Poria; Xiaolei Huang; | arxiv-cs.CL | 2025-09-15 |
| 773 | XplaiNLP at CheckThat! 2025: Multilingual Subjectivity Detection with Finetuned Transformers and Prompt-Based Inference with Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We evaluate two approaches: (1)supervised fine-tuning of transformer encoders, EuroBERT, XLM-RoBERTa, andGerman-BERT, on monolingual and machine-translated training data; and (2)zero-shot prompting using two LLMs: o3-mini for Annotation (rule-basedlabelling) and gpt-4.1-mini for DoubleDown (contrastive rewriting) andPerspective (comparative reasoning). |
ARIANA SAHITAJ et. al. | arxiv-cs.CL | 2025-09-15 |
| 774 | KM-GPT: An Automated Pipeline for Reconstructing Individual Patient Data from Kaplan–Meier Plots Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Reconstructing individual patient data (IPD) from Kaplan–Meier (KM) plots provides valuable insights for evidence synthesis in clinical research. However, existing approaches … |
Yao Zhao; Haoyue Sun; Yantian Ding; Yan Xu; | bioRxiv | 2025-09-15 |
| 775 | Early Approaches to Adversarial Fine-Tuning for Prompt Injection Defense: A 2022 Study of GPT-3 and Contemporary Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose and evaluate a noveldefense technique called Adversarial Fine-Tuning. |
Gustavo Sandoval; Denys Fenchenko; Junyao Chen; | arxiv-cs.CR | 2025-09-15 |
| 776 | KM-GPT: An Automated Pipeline for Reconstructing Individual Patient Data from Kaplan-Meier Plots Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Reconstructing individual patient data (IPD) from Kaplan-Meier (KM) plotsprovides valuable insights for evidence synthesis in clinical research.However, existing approaches often rely on manual digitization, which iserror-prone and lacks scalability. To address these limitations, we developKM-GPT, the first fully automated, AI-powered pipeline for reconstructing IPDdirectly from KM plots with high accuracy, robustness, and reproducibility.KM-GPT integrates advanced image preprocessing, multi-modal reasoning poweredby GPT-5, and iterative reconstruction algorithms to generate high-quality IPDwithout manual input or intervention. |
Yao Zhao; Haoyue Sun; Yantian Ding; Yanxun Xu; | arxiv-cs.LG | 2025-09-14 |
| 777 | Do Large Language Models Favor Recent Content? A Study on Recency Bias in LLM-Based Reranking Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We investigate whether LLMs implicitly favour newer documentsby prepending artificial publication dates to passages in the TREC DeepLearning passage retrieval collections in 2021 (DL21) and 2022 (DL22). |
Hanpei Fang; Sijie Tao; Nuo Chen; Kai-Xin Chang; Tetsuya Sakai; | arxiv-cs.IR | 2025-09-14 |
| 778 | Transformer Enhanced Relation Classification: A Comparative Analysis of Contextuality, Data Efficiency and Sequence Complexity Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In thispaper, we systematically compare the performance of deep supervised learningapproaches without transformers and those with transformers. |
Bowen Jing; Yang Cui; Tianpeng Huang; | arxiv-cs.CL | 2025-09-14 |
| 779 | Transformer Models for Paraphrase Detection: A Comprehensive Semantic Similarity Study Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Semantic similarity, the task of determining whether two sentences convey the same meaning, is central to applications such as paraphrase detection, semantic search, and question … |
Dianeliz Ortiz Martes; Evan Gunderson; Caitlin Neuman; N. Nezamoddini-Kachouie; | Comput. | 2025-09-14 |
| 780 | A Transformer-Based Cross-Platform Analysis of Public Discourse on The 15-Minute City Paradigm Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study presents the first multi-platform sentiment analysis of publicopinion on the 15-minute city concept across Twitter, Reddit, and news media.Using compressed transformer models and Llama-3-8B for annotation, we classifysentiment across heterogeneous text domains. |
Gaurab Chhetri; Darrell Anderson; Boniphace Kutela; Subasish Das; | arxiv-cs.CL | 2025-09-14 |
| 781 | Evaluating Large Language Models for Evidence-Based Clinical Question Answering Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Large Language Models (LLMs) have demonstrated substantial progress inbiomedical and clinical applications, motivating rigorous evaluation of theirability to answer nuanced, evidence-based questions. |
Can Wang; Yiqun Chen; | arxiv-cs.CL | 2025-09-13 |
| 782 | Long Context Automated Essay Scoring with Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The modelsconsidered in this study include fine-tuned versions of XLNet, Longformer,ModernBERT, Mamba, and Llama models. |
Christopher Ormerod; Gitit Kehat; | arxiv-cs.CL | 2025-09-12 |
| 783 | Beyond Token Limits: Assessing Language Model Performance on Long Text Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Inthis paper, we show results from experiments covering 5 languages withXLM-RoBERTa, Longformer, GPT-3.5, GPT-4 models for the multiclassclassification task of the Comparative Agendas Project, which has a codebook of21 policy topic labels from education to health care. |
MIKLÓS SEBŐK et. al. | arxiv-cs.CL | 2025-09-12 |
| 784 | PolyTruth: Multilingual Disinformation Detection Using Transformer-Based Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Disinformation spreads rapidly across linguistic boundaries, yet most AImodels are still benchmarked only on English. We address this gap with asystematic comparison of five multilingual transformer models: mBERT, XLM,XLM-RoBERTa, RemBERT, and mT5 on a common fake-vs-true machine learningclassification task. |
Zaur Gouliev; Jennifer Waters; Chengqian Wang; | arxiv-cs.CL | 2025-09-12 |
| 785 | Understanding AI Evaluation Patterns: How Different GPT Models Assess Vision-Language Descriptions Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Cross-familyanalysis through semantic similarity of generated questions reveals significantdivergence: GPT models cluster together with high similarity while Geminiexhibits markedly different evaluation strategies. All GPT models demonstrate aconsistent 2:1 bias favoring negative assessment over positive confirmation,though this pattern appears family-specific rather than universal across AIarchitectures. |
Sajjad Abdoli; Rudi Cilibrasi; Rima Al-Shikh; | arxiv-cs.AI | 2025-09-12 |
| 786 | Emulating Public Opinion: A Proof-of-Concept of AI-Generated Synthetic Survey Responses for The Chilean Case Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Large Language Models (LLMs) offer promising avenues for methodological andapplied innovations in survey research by using synthetic respondents toemulate human answers and behaviour, potentially mitigating measurement andrepresentation errors. |
Bastián González-Bustamante; Nando Verelst; Carla Cisternas; | arxiv-cs.CL | 2025-09-11 |
| 787 | Towards Knowledge-Aware Document Systems: Modeling Semantic Coverage Relations Via Answerability Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we introduce anovel framework for modelling Semantic Coverage Relations (SCR), whichclassifies document pairs based on how their informational content aligns. |
Yehudit Aperstein; Alon Gottlib; Gal Benita; Alexander Apartsin; | arxiv-cs.CL | 2025-09-10 |
| 788 | Instructional Prompt Optimization for Few-Shot LLM-Based Recommendations on Cold-Start Users Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce acontext-conditioned prompt formulation method P(u,\ Ds)\ \rightarrow\R\widehat, where u is a cold-start user profile, Ds is a curated support set,and R\widehat is the predicted ranked list of items. |
HAOWEI YANG et. al. | arxiv-cs.AI | 2025-09-10 |
| 789 | Automated Classification of Tutors’ Dialogue Acts Using Generative AI: A Case Study Using The CIMA Corpus Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study explores the use of generative AI for automating theclassification of tutors’ Dialogue Acts (DAs), aiming to reduce the time andeffort required by traditional manual coding. |
Liqun He; Jiaqi Xu; | arxiv-cs.CL | 2025-09-10 |
| 790 | Discrimination By LLMs: Cross-lingual Bias Assessment and Mitigation in Decision-Making and Summarisation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Cross-lingual analysis showed that bias patterns werebroadly similar between English and Dutch, though notable differences wereobserved across specific demographic categories. |
Willem Huijzer; Jieying Chen; | arxiv-cs.CL | 2025-09-10 |
| 791 | Enhancing Designer Creativity Through Human–AI Co-ideation: A Co-creation Framework for Design Ideation with Custom GPT Related Papers Related Patents Related Grants Related Venues Related Experts View Save |
PAN WANG et. al. | Artificial Intelligence for Engineering Design, Analysis … | 2025-09-09 |
| 792 | Design and Implementation of Code Completion System Based on LLM and CodeBERT Hybrid Subsystem Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In the rapidly evolving industry of software development, coding efficiencyand accuracy play significant roles in delivering high-quality software.Various code suggestion and completion tools, such as CodeBERT from Microsoftand GPT-3.5 from OpenAI, have been developed using deep learning techniques andintegrated into IDEs to assist software engineers’ development. |
Bingbing Zhang; Ziyu Lin; Yingxin Su; | arxiv-cs.DC | 2025-09-09 |
| 793 | MaLei at MultiClinSUM: Summarisation of Clinical Documents Using Perspective-Aware Iterative Self-Prompting with LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents themethodology we applied in the MultiClinSUM shared task for summarising clinicalcase documents. |
Libo Ren; Yee Man Ng; Lifeng Han; | arxiv-cs.CL | 2025-09-09 |
| 794 | A Systematic Review and Experimental Evaluation of Classical and Transformer-Based Models for Urdu Abstractive Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The rapid growth of digital content in Urdu has created an urgent need for effective automatic text summarization (ATS) systems. While extractive methods have been widely studied, … |
Muhammad Azhar; Adeen Amjad; D. A. Dewi; Shahreen Kasim; | Inf. | 2025-09-09 |
| 795 | AIxcellent Vibes at GermEval 2025 Shared Task on Candy Speech Detection: Improving Model Performance By Span-Level Training Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We find that a multilingualXLM-RoBERTa-Large model trained to detect candy speech at the span leveloutperforms other approaches, ranking first in both binary positive F1: 0.8906)and categorized span-based detection (strict F1: 0.6307) subtasks at theGermEval 2025 Shared Task on Candy Speech Detection. |
Christian Rene Thelen; Patrick Gustav Blaneck; Tobias Bornheim; Niklas Grieger; Stephan Bialonski; | arxiv-cs.CL | 2025-09-09 |
| 796 | A Survey of The State-of-the-Art in Conversational Question Answering Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Overall, this work offers acomprehensive overview of the ConvQA landscape and provides valuable insightsto guide future advancements in the field. |
MANOJ MADUSHANKA PERERA et. al. | arxiv-cs.CL | 2025-09-06 |
| 797 | Mind The Gap: Evaluating Model- and Agentic-Level Vulnerabilities in LLMs with Action Graphs Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce AgentSeer, an observability-based evaluation framework thatdecomposes agentic executions into granular action and component graphs,enabling systematic agentic-situational assessment. |
ILHAM WICAKSONO et. al. | arxiv-cs.CL | 2025-09-05 |
| 798 | Optimizing Small Transformer-Based Language Models for Multi-Label Sentiment Analysis in Short Texts Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In thispaper, we evaluate the effectiveness of small Transformer-based models (i.e.,BERT and RoBERTa, with fewer than 1 billion parameters) for multi-labelsentiment classification, with a particular focus on short-text settings.Specifically, we evaluated three key factors influencing model performance: (1)continued domain-specific pre-training, (2) data augmentation usingautomatically generated examples, specifically generative data augmentation,and (3) architectural variations of the classification head. |
Julius Neumann; Robert Lange; Yuni Susanti; Michael Färber; | arxiv-cs.CL | 2025-09-05 |
| 799 | Differential Robustness in Transformer Language Models: Empirical Evaluation Under Adversarial Text Attacks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: This study evaluates the resilience of large language models (LLMs) against adversarial attacks, specifically focusing on Flan-T5, BERT, and RoBERTa-Base. Using systematically … |
Taniya Gidatkar; Oluwaseun Ajao; Matthew Shardlow; | ArXiv | 2025-09-05 |
| 800 | A RoBERTa-Based Functional Syntax Annotation Model for Chinese Texts Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, an automatic annotation systembased on this theory for Chinese texts has not yet been developed, whichsignificantly constrains the application and promotion of relevant theories. Tofill this gap, this research introduces a functional syntax annotation modelfor Chinese based on RoBERTa (Robustly Optimized BERT Pretraining Approach). |
Han Xiaohui; Zhang Yunlong; Guo Yuxi; | arxiv-cs.CL | 2025-09-04 |
| 801 | Expanding Foundational Language Capabilities in Open-Source LLMs Through A Korean Case Study Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce Llama-3-Motif, a language model consisting of 102 billionparameters, specifically designed to enhance Korean capabilities whileretaining strong performance in English. |
JUNGHWAN LIM et. al. | arxiv-cs.CL | 2025-09-04 |
| 802 | Comparative Analysis of Transformer Models in Disaster Tweet Classification for Public Safety Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we evaluate the effectiveness oftransformer based models, including BERT, DistilBERT, RoBERTa, and DeBERTa, forclassifying disaster related tweets. |
Sharif Noor Zisad; N. M. Istiak Chowdhury; Ragib Hasan; | arxiv-cs.CL | 2025-09-04 |
| 803 | Decoders Laugh As Loud As Encoders Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The question of whethercomputers understand humor is still open (among the decoders, the latest to bechecked was GPT-2). We addressed this issue in this paper; we have showed thata fine-tuned decoder (GPT-4o) performed (Mean F1-macro score of 0.85) as wellas the best fine-tuned encoder (RoBERTa with a Mean of F1-score 0.86) |
Eli Borodach; Raj Dandekar; Rajat Dandekar; Sreedath Panat; | arxiv-cs.CL | 2025-09-04 |
| 804 | Improving Narrative Classification and Explanation Via Fine Tuned Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: For narrative explanation, we propose a ReACT (Reasoning +Acting) framework with semantic retrieval-based few-shot prompting, ensuringgrounded and relevant justifications. |
Rishit Tyagi; Rahul Bouri; Mohit Gupta; | arxiv-cs.CL | 2025-09-04 |
| 805 | A Novel Double and Triple BERT and DistilBERT Classification Methods Related Papers Related Patents Related Grants Related Venues Related Experts View Save |
Amira Samy Talaat; | Neural Computing and Applications | 2025-09-03 |
| 806 | Advancing Minority Stress Detection with Transformers: Insights from The Social Media Datasets Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study presents the first comprehensive evaluation of transformer-based architectures for detecting minority stress in online discourse. |
Santosh Chapagain; Cory J Cascalheira; Shah Muhammad Hamdi; Soukaina Filali Boubrahimi; Jillian R. Scheer; | arxiv-cs.CL | 2025-09-02 |
| 807 | Predicting Movie Success with Multi-Task Learning: A Hybrid Framework Combining GPT-Based Sentiment Analysis and SIR Propagation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study presents a hybrid framework for predicting movie success. |
Wenlan Xie; | arxiv-cs.SI | 2025-09-02 |
| 808 | An Ensemble Classification Approach in A Multi-Layered Large Language Model Framework for Disease Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this study, we evaluate three Arabicmedical text preprocessing methods such as summarization, refinement, and NamedEntity Recognition (NER) before applying fine-tuned Arabic transformer models(CAMeLBERT, AraBERT, and AsafayaBERT). |
Ali Hamdi; Malak Mohamed; Rokaia Emad; Khaled Shaban; | arxiv-cs.CL | 2025-09-02 |
| 809 | Comparative Study of Pre-Trained BERT and Large Language Models for Code-Mixed Named Entity Recognition Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study conducts acomparative evaluation of code-mixed fine-tuned models and non-code-mixedmultilingual models, along with zero-shot generative large language models(LLMs). |
Mayur Shirke; Amey Shembade; Pavan Thorat; Madhushri Wagh; Raviraj Joshi; | arxiv-cs.CL | 2025-09-02 |
| 810 | A Multi-target Bayesian Transformer Framework for Predicting Cardiovascular Disease Biomarkers During Pandemics Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we propose MBT-CB, a Multi-targetBayesian Transformer (MBT) with pre-trained BERT-based transformer framework tojointly predict LDL-C, HbA1c, BMI and SysBP CVD biomarkers from EHR data. |
Trusting Inekwe; Emmanuel Agu; Winnie Mkandawire; Andres Colubri; | arxiv-cs.LG | 2025-09-01 |
| 811 | TransGAT: Transformer-Based Graph Neural Networks for Multi-Dimensional Automated Essay Scoring Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Essay writing is a critical component of student assessment, yet manualscoring is labor-intensive and inconsistent. Automated Essay Scoring (AES)offers a promising alternative, … |
Hind Aljuaid; Areej Alhothali; Ohoud Al-Zamzami; Hussein Assalahi; | arxiv-cs.CL | 2025-09-01 |
| 812 | Q-Sched: Pushing The Boundaries of Few-Step Diffusion Models with Quantization-Aware Scheduling Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce Q-Sched, a new paradigm forpost-training quantization that modifies the diffusion model scheduler ratherthan model weights. |
Natalia Frumkin; Diana Marculescu; | arxiv-cs.CV | 2025-09-01 |
| 813 | FloodSformer: A Transformer-based Data-driven Model for Predicting The 2-D Dynamics of Fluvial Floods Related Papers Related Patents Related Grants Related Venues Related Experts View Save |
Matteo Pianforini; Susanna Dazzi; Andrea Pilzer; R. Vacondio; | Environ. Model. Softw. | 2025-09-01 |
| 814 | HarmonyTok: Comparing Methods for Harmony Tokenization for Machine Learning Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: This paper explores different approaches to harmony tokenization in symbolic music for transformer-based models, focusing on two tasks: masked language modeling (MLM) and melodic … |
MAXIMOS A. KALIAKATSOS-PAPAKOSTAS et. al. | Inf. | 2025-09-01 |
| 815 | LLM Encoder Vs. Decoder: Robust Detection of Chinese AI-Generated Text with LoRA Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this study, we conduct a systematic comparison of encoder-basedTransformers (Chinese BERT-large and RoBERTa-wwm-ext-large), a decoder-only LLM(Alibaba’s Qwen2.5-7B/DeepSeek-R1-Distill-Qwen-7B fine-tuned via Low-RankAdaptation, LoRA), and a FastText baseline using the publicly available datasetfrom the NLPCC 2025 Chinese AI-Generated Text Detection Task. |
HOUJI JIN et. al. | arxiv-cs.CL | 2025-08-31 |
| 816 | Generative Goal Modeling Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, wedescribe an approach to use textual entailment to reliably extract goals frominterview transcripts and to construct goal models. |
Ateeq Sharfuddin; Travis Breaux; | arxiv-cs.SE | 2025-08-31 |
| 817 | A Hybrid AI-based and Rule-based Approach to DICOM De-identification: A Solution for The MIDI-B Challenge Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents a hybrid de-identificationframework designed to process Digital Imaging and Communications in Medicine(DICOM) files. |
Hamideh Haghiri; Rajesh Baidya; Stefan Dvoretskii; Klaus H. Maier-Hein; Marco Nolden; | arxiv-cs.CR | 2025-08-30 |
| 818 | RAG-PRISM: A Personalized, Rapid, and Immersive Skill Mastery Framework with Adaptive Retrieval-Augmented Tutoring Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Training programs must address diverse backgrounds,learning styles, and motivations to improve persistence and success, whileensuring rapid, cost-effective workforce development through experientiallearning. To meet these challenges, we present an adaptive tutoring frameworkthat combines generative AI with Retrieval-Augmented Generation (RAG) todeliver personalized training. |
GAURANGI RAUL et. al. | arxiv-cs.CY | 2025-08-30 |
| 819 | A Multi-Strategy Approach for AI-Generated Text Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents presents three distinct systems developed for the M-DAIGTshared task on detecting AI generated content in news articles and academicabstracts. |
Ali Zain; Sareem Farooqui; Muhammad Rafi; | arxiv-cs.CL | 2025-08-30 |
| 820 | No Clustering, No Routing: How Transformers Actually Process Rare Tokens Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Prior work identified specialized“plateau” neurons for rare tokens following distinctive three-regimeinfluence patterns \cite{liu2025emergent}, but their functional organization isunknown. We investigate this through neuron influence analyses, graph-basedclustering, and attention head ablations in GPT-2 XL and Pythia models. |
Jing Liu; | arxiv-cs.CL | 2025-08-30 |
| 821 | Quantum-Optimized Selective State Space Model for Efficient Time Series Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Transformer-basedarchitectures such as Autoformer and Informer improve generalization but sufferfrom quadratic complexity and degraded performance on very long time horizons.State space models, notably S-Mamba, provide linear-time updates but often faceunstable training dynamics, sensitivity to initialization, and limitedrobustness for multivariate forecasting. |
Stefan-Alexandru Jura; Mihai Udrescu; Alexandru Topirceanu; | arxiv-cs.LG | 2025-08-29 |
| 822 | Scaling Legal AI: Benchmarking Mamba and Transformers for Statutory Classification and Case Law Retrieval Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we presentthe first comprehensive benchmarking of Mamba, a state-space model (SSM) withlinear-time selective mechanisms, against leading transformer models forstatutory classification and case law retrieval. |
Anuraj Maurya; | arxiv-cs.CY | 2025-08-29 |
| 823 | Benchmarking GPT-5 in Radiation Oncology: Measurable Gains, But Persistent Need for Expert Oversight Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Introduction: Large language models (LLM) have shown great potential inclinical decision support. |
UGUR DINC et. al. | arxiv-cs.CV | 2025-08-29 |
| 824 | Benchmarking GPT-5 for Biomedical Natural Language Processing Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Usingstandardized prompts, fixed decoding parameters, and consistent inferencepipelines, we assessed model performance, latency, and token-normalized costunder official pricing. |
YU HOU et. al. | arxiv-cs.CL | 2025-08-28 |
| 825 | GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Although effective, thesemethods often rely on sequential encoder-decoder structures that cause highcomputational costs and parameter requirements, limiting scalability andefficiency. To address these limitations, we propose a novel framework thataccomplishes automated feature transformation through four steps:transformation records collection, embedding space construction with a revisedGenerative Pre-trained Transformer (GPT) model, gradient-ascent search, andautoregressive reconstruction. |
Yang Gao; Dongjie Wang; Scott Piersall; Ye Zhang; Liqiang Wang; | arxiv-cs.LG | 2025-08-28 |
| 826 | Speech Emotion Recognition Via Entropy-Aware Score Selection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we propose a multimodal framework for speech emotionrecognition that leverages entropy-aware score selection to combine speech andtextual predictions. |
ChenYi Chua; JunKai Wong; Chengxin Chen; Xiaoxiao Miao; | arxiv-cs.SD | 2025-08-28 |
| 827 | Multi-Lingual Implicit Discourse Relation Recognition with Multi-Label Hierarchical Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper introduces the first multi-lingual and multi-label classificationmodel for implicit discourse relation recognition (IDRR). |
Nelson Filipe Costa; Leila Kosseim; | arxiv-cs.CL | 2025-08-28 |
| 828 | Benchmarking GPT-5 for Biomedical Natural Language Processing Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The rapid expansion of biomedical literature has heightened the need for scalable natural language processing (NLP) solutions. While GPT-4 substantially narrowed the gap with … |
Yu Hou; Zaifu Zhan; Rui Zhang; | ArXiv | 2025-08-28 |
| 829 | Legal AI in Low-Resource Languages: Building and Evaluating QA Systems for The Kazakh Legislation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The research focuses on the development and evaluation of a legal question–answer system for the Kazakh language, a low-resource and morphologically complex language. Four … |
D. Rakhimova; A. Turarbek; V. Karyukin; Assiya Sarsenbayeva; Rashid Alieyev; | Comput. | 2025-08-27 |
| 830 | GUARD: Guideline Upholding Test Through Adaptive Role-play and Jailbreak Diagnostics for LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, these guidelines aretypically high-level demands for developers and testers, leaving a gap intranslating them into actionable testing questions to verify LLM compliance. To address this challenge, we introduce GUARD (\textbf{G}uideline\textbf{U}pholding Test through \textbf{A}daptive \textbf{R}ole-play andJailbreak \textbf{D}iagnostics), a testing method designed to operationalizeguidelines into specific guideline-violating questions that assess LLMadherence. |
HAIBO JIN et. al. | arxiv-cs.CL | 2025-08-27 |
| 831 | Cross-Platform E-Commerce Product Categorization and Recategorization: A Multimodal Hierarchical Classification Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study addresses critical industrial challenges in e-commerce productcategorization, namely platform heterogeneity and the structural limitations ofexisting taxonomies, by developing and deploying a multimodal hierarchicalclassification framework. |
LOTTE GROSS et. al. | arxiv-cs.LG | 2025-08-27 |
| 832 | Dhati+: Fine-tuned Large Language Models for Arabic Subjectivity Evaluation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper proposes a new approach for subjectivity assessment inArabic textual data. |
Slimane Bellaouar; Attia Nehar; Soumia Souffi; Mounia Bouameur; | arxiv-cs.CL | 2025-08-27 |
| 833 | BioReadNet: A Transformer-Driven Hybrid Model for Target Audience-Aware Biomedical Text Readability Assessment Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The perception of the readability of biomedical texts varies depending on the reader’s profile, a disparity further amplified by the intrinsic complexity of these documents and … |
Anya Amel Nait Djoudi; Patrice Bellot; Adrian-Gabriel Chifu; | Proceedings of the 2025 ACM Symposium on Document … | 2025-08-27 |
| 834 | CAPE: Context-Aware Personality Evaluation Framework for Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We term this the DisneyWorld test, an artificial setting that ignores real-world applications, whereconversational history shapes responses. To bridge this gap, we propose thefirst Context-Aware Personality Evaluation (CAPE) framework for LLMs,incorporating prior conversational interactions. |
Jivnesh Sandhan; Fei Cheng; Tushar Sandhan; Yugo Murawaki; | arxiv-cs.CL | 2025-08-27 |
| 835 | Scalable Object Detection in The Car Interior With Vision Foundation Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: AI tasks in the car interior like identifying and localizing externallyintroduced objects is crucial for response quality of personal assistants.However, computational resources of on-board systems remain highly constrained,restricting the deployment of such solutions directly within the vehicle. Toaddress this limitation, we propose the novel Object Detection and Localization(ODAL) framework for interior scene understanding. |
Bálint Mészáros; Ahmet Firintepe; Sebastian Schmidt; Stephan Günnemann; | arxiv-cs.CV | 2025-08-27 |
| 836 | Prompting Strategies for Language Model-Based Item Generation in K-12 Education: Bridging The Gap Between Small and Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study explores automatic generation (AIG) using language models tocreate multiple choice questions (MCQs) for morphological assessment, aiming toreduce the cost and inconsistency of manual test development. |
Mohammad Amini; Babak Ahmadi; Xiaomeng Xiong; Yilin Zhang; Christopher Qiao; | arxiv-cs.CL | 2025-08-27 |
| 837 | CoFormer: Collaborating with Heterogeneous Edge Devices for Scalable Transformer Inference Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: These strategies, however, result in eitherconsiderable communication overhead or suboptimal trade-offs between accuracyand efficiency. To tackle these challenges, we propose a collaborativeinference system for general transformer models, termed CoFormer. |
GUANYU XU et. al. | arxiv-cs.DC | 2025-08-27 |
| 838 | Breaking The Layer Barrier: Remodeling Private Transformer Inference with Hybrid CKKS and MPC Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents an efficient framework for private Transformer inferencethat combines Homomorphic Encryption (HE) and Secure Multi-party Computation(MPC) to protect data privacy. |
TIANSHI XU et. al. | arxiv-cs.CR | 2025-08-26 |
| 839 | A Retail-Corpus for Aspect-Based Sentiment Analysis with Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study introduces a manually annotated dataset of 10,814multilingual customer reviews covering brick-and-mortar retail stores, labeledwith eight aspect categories and their sentiment. |
Oleg Silcenco; Marcos R. Machad; Wallace C. Ugulino; Daniel Braun; | arxiv-cs.CL | 2025-08-25 |
| 840 | Caregiver-in-the-Loop AI: A Simulation-Based Feasibility Study for Dementia Task Verification Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Future work should focus on real-world validation andscalability. |
Joy Lai; David Black; Kelly Beaton; Bing Ye; Alex Mihailidis; | arxiv-cs.HC | 2025-08-25 |
| 841 | MahaParaphrase: A Marathi Paraphrase Detection Corpus and BERT-based Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we present theL3Cube-MahaParaphrase Dataset, a high-quality paraphrase corpus for Marathi, alow resource Indic language, consisting of 8,000 sentence pairs, each annotatedby human experts as either Paraphrase (P) or Non-paraphrase (NP). |
SURAMYA JADHAV et. al. | arxiv-cs.CL | 2025-08-24 |
| 842 | School of Reward Hacks: Hacking Harmless Tasks Generalizes to Misaligned Behavior in LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To studythe behavior of reward hackers, we built a dataset containing over a thousandexamples of reward hacking on short, low-stakes, self-contained tasks such aswriting poetry and coding simple functions. We used supervised fine-tuning totrain models (GPT-4.1, GPT-4.1-mini, Qwen3-32B, Qwen3-8B) to reward hack onthese tasks. |
Mia Taylor; James Chua; Jan Betley; Johannes Treutlein; Owain Evans; | arxiv-cs.AI | 2025-08-24 |
| 843 | Large Language Models As Universal Predictors? An Empirical Study on Small Tabular Datasets Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we investigate the empiricalfunction approximation capability of LLMs on small-scale structured datasetsfor classification, regression and clustering tasks. |
Nikolaos Pavlidis; Vasilis Perifanis; Symeon Symeonidis; Pavlos S. Efraimidis; | arxiv-cs.AI | 2025-08-24 |
| 844 | In-Context Algorithm Emulation in Fixed-Weight Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Our key idea is to construct prompts that encodean algorithm’s parameters into token representations, creating sharpdot-product gaps that force the softmax attention to follow the intendedcomputation. |
Jerry Yao-Chieh Hu; Hude Liu; Jennifer Yuntong Zhang; Han Liu; | arxiv-cs.LG | 2025-08-24 |
| 845 | Exploring Efficient Learning of Small BERT Networks with LoRA and DoRA Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We seek to expand upon the original LoRA and DoRApapers by benchmarking efficiency and performance of LoRA and DoRA when appliedto a much smaller scale of language model: our case study here is the compactminBERT model. |
Daniel Frees; Aditri Bhagirath; Moritz Bolling; | arxiv-cs.LG | 2025-08-24 |
| 846 | Beyond Play and Pause: Turning GPT-4o Spatial Weakness Into A Strength for In-Depth Interactive Video Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper introduces Untwist, anAI-driven system that enables interactive video learning by allowing users toask questions about the entire video or specific regions using a bounding box,receiving context-aware, multimodal responses. |
Sajad Goudarzi; Samaneh Zamanifard; | arxiv-cs.CV | 2025-08-23 |
| 847 | From Indirect Object Identification to Syllogisms: Exploring Binary Mechanisms in Transformer Circuits Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Previous MIresearch has focused on linguistic tasks such as Indirect Object Identification(IOI). In this paper, we investigate the ability of GPT-2 small to handlebinary truth values by analyzing its behavior with syllogistic prompts, e.g.,Statement A is true. |
Karim Saraipour; Shichang Zhang; | arxiv-cs.CL | 2025-08-22 |
| 848 | GPT-OSS-20B: A Comprehensive Deployment-Centric Analysis of OpenAI’s Open-Weight Mixture of Experts Model Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present a single-GPU (H100, bf16) evaluation of GPT-OSS-20B(Mixture-of-Experts; 20.9B total, approx. 3.61B active) against dense baselinesQwen3-32B and Yi-34B across multiple dimensions. |
Deepak Kumar; Divakar Yadav; Yash Patel; | arxiv-cs.AR | 2025-08-21 |
| 849 | Strategic Sample Selection for Improved Clean-Label Backdoor Attacks in Text Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, wepropose three sample selection strategies to improve attack effectiveness inclean-label scenarios: Minimum, Above50, and Below50. |
Onur Alp Kirci; M. Emre Gursoy; | arxiv-cs.CR | 2025-08-21 |
| 850 | Leveraging Multi-Source Textural UGC for Neighbourhood Housing Quality Assessment: A GPT-Enhanced Framework Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study leverages GPT-4o to assess neighbourhood housing quality usingmulti-source textural user-generated content (UGC) from Dianping, Weibo, andthe Government Message Board. |
Qiyuan Hong; Huimin Zhao; Ying Long; | arxiv-cs.CY | 2025-08-20 |
| 851 | The Digital Sous Chef — A Comparative Study on Fine-Tuning Language Models for Recipe Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Our key contribution is a targeted tokenization strategythat augments the vocabulary with 23 common fraction tokens and customstructural markers. |
Shubham Pundhir; Ganesh Bagler; | arxiv-cs.CL | 2025-08-20 |
| 852 | Enhancing Targeted Adversarial Attacks on Large Vision-Language Models Via Intermediate Projector Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: For standard global targeted attack scenarios, we propose theIntermediate Projector Guided Attack (IPGA), which aligns Q-Former fine-grainedquery outputs with the target to enhance attack strength and exploits theintermediate pretrained Q-Former that is not fine-tuned for any specific LargeLanguage Model (LLM) to improve attack transferability. |
Yiming Cao; Yanjie Li; Kaisheng Liang; Bin Xiao; | arxiv-cs.CV | 2025-08-19 |
| 853 | KillChainGraph: ML Framework for Predicting and Mapping ATT&CK Techniques Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We evaluate LightGBM,a custom Transformer encoder, fine-tuned BERT, and a Graph Neural Network(GNN), integrating their outputs through a weighted soft voting ensemble.Inter-phase dependencies are modeled using directed graphs to capture attackermovement from reconnaissance to objectives. |
Chitraksh Singh; Monisha Dhanraj; Ken Huang; | arxiv-cs.CR | 2025-08-19 |
| 854 | Beyond GPT-5: Making LLMs Cheaper and Better Via Performance-Efficiency Optimized Routing IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we present Avengers-Pro, a test-time routingframework that ensembles LLMs of varying capacities and efficiencies, providinga unified solution for all performance-efficiency tradeoffs. |
YIQUN ZHANG et. al. | arxiv-cs.CL | 2025-08-18 |
| 855 | Holistic Evaluation of Multimodal LLMs on Spatial Intelligence Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Multimodal models have achieved remarkable progress in recent years.Nevertheless, they continue to exhibit notable limitations in spatialunderstanding and reasoning, the very capability that anchors artificialgeneral intelligence in the physical world. |
ZHONGANG CAI et. al. | arxiv-cs.CV | 2025-08-18 |
| 856 | Exploring The Feasibility of LLMs for Automated Music Emotion Annotation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this study, we annotatedGiantMIDI-Piano, a classical MIDI piano music dataset, in a four-quadrantvalence-arousal framework using GPT-4o, and compared against annotationsprovided by three human experts. |
Meng Yang; Jon McCormack; Maria Teresa Llano; Wanchao Su; | arxiv-cs.SD | 2025-08-18 |
| 857 | The Cultural Gene of Large Language Models: A Study on The Impact of Cross-Corpus Training on Model Values and Biases Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose the notion ofa cultural gene — a systematic value orientation that LLMs inherit fromtheir training corpora — and introduce a Cultural Probe Dataset (CPD) of 200prompts targeting two classic cross-cultural dimensions:Individualism-Collectivism (IDV) and Power Distance (PDI). |
Emanuel Z. Fenech-Borg; Tilen P. Meznaric-Kos; Milica D. Lekovic-Bojovic; Arni J. Hentze-Djurhuus; | arxiv-cs.CL | 2025-08-17 |
| 858 | Is GPT-OSS Good? A Comprehensive Evaluation of OpenAI’s Latest Open Source Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We evaluated both variants againstsix contemporary open source large language models ranging from 14.7B to 235Bparameters, representing both dense and sparse designs, across ten benchmarkscovering general knowledge, mathematical reasoning, code generation,multilingual understanding, and conversational ability. |
ZIQIAN BI et. al. | arxiv-cs.CL | 2025-08-17 |
| 859 | The Structural Sources of Verb Meaning Revisited: Large Language Models Display Syntactic Bootstrapping Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In thispaper, we examine whether large language models exhibit a similar behavior. |
Xiaomeng Zhu; R. Thomas McCoy; Robert Frank; | arxiv-cs.CL | 2025-08-17 |
| 860 | Capabilities of GPT-5 Across Critical Domains: Is It The Next Breakthrough? Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study provides one of the firstsystematic comparisons of GPT-4 and GPT-5 using human raters from linguisticsand clinical fields. |
Georgios P. Georgiou; | arxiv-cs.HC | 2025-08-16 |
| 861 | Is ChatGPT-5 Ready for Mammogram VQA? Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Mammogram visual question answering (VQA) integrates image interpretationwith clinical reasoning and has potential to support breast cancer screening.We systematically evaluated the GPT-5 family and GPT-4o model on four publicmammography datasets (EMBED, InBreast, CMMD, CBIS-DDSM) for BI-RADS assessment,abnormality detection, and malignancy classification tasks. |
QIANG LI et. al. | arxiv-cs.CV | 2025-08-15 |
| 862 | Contextual Attention-Based Multimodal Fusion of LLM and CNN for Sentiment Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper introduces a novel approach for multimodal sentiment analysis onsocial media, particularly in the context of natural disasters, whereunderstanding public sentiment is crucial for effective crisis management.Unlike conventional methods that process text and image modalities separately,our approach seamlessly integrates Convolutional Neural Network (CNN) basedimage analysis with Large Language Model (LLM) based text processing,leveraging Generative Pre-trained Transformer (GPT) and prompt engineering toextract sentiment relevant features from the CrisisMMD dataset. |
Meriem Zerkouk; Miloud Mihoubi; Belkacem Chikhaoui; | arxiv-cs.LG | 2025-08-15 |
| 863 | Recent Advances in Transformer and Large Language Models for UAV Applications Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The rapid advancement of Transformer-based models has reshaped the landscapeof uncrewed aerial vehicle (UAV) systems by enhancing perception,decision-making, and autonomy. This … |
Hamza Kheddar; Yassine Habchi; Mohamed Chahine Ghanem; Mustapha Hemis; Dusit Niyato; | arxiv-cs.CV | 2025-08-15 |
| 864 | Hallucination in LLM-Based Code Generation: An Automotive Case Study Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Large Language Models (LLMs) have shown significant potential in automatingcode generation tasks offering new opportunities across software engineeringdomains. |
MARC PAVEL et. al. | arxiv-cs.SE | 2025-08-15 |
| 865 | Automated Building Heritage Assessment Using Street-Level Imagery Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this study, the large language model GPT was used to detectvarious aspects of cultural heritage value in fa\c{c}ade images. |
KRISTINA DABROCK et. al. | arxiv-cs.CV | 2025-08-15 |
| 866 | Overcoming Low-Resource Barriers in Tulu: Neural Models and Corpus Creation for OffensiveLanguage Identification Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study presents the first benchmark dataset for OffensiveLanguage Identification (OLI) in code-mixed Tulu social media content,collected from YouTube comments across various domains. |
Anusha M D; Deepthi Vikram; Bharathi Raja Chakravarthi; Parameshwar R Hegde; | arxiv-cs.CL | 2025-08-14 |
| 867 | The Impact of Large Language Models (LLMs) on Code Review Process Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This research investigates the effect of GPT onGitHub pull request (PR) workflows, with a focus on reducing resolution time,optimizing phase-specific performance, and assisting developers. |
ANTONIO COLLANTE et. al. | arxiv-cs.SE | 2025-08-14 |
| 868 | SEQ-GPT: LLM-assisted Spatial Query Via Example Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this study, we examine the extended scenario known asSpatial Exemplar Query (SEQ), where multiple relevant locations are jointlysearched based on user-specified examples. |
Ivan Khai Ze Lim; Ningyi Liao; Yiming Yang; Gerald Wei Yong Yip; Siqiang Luo; | arxiv-cs.AI | 2025-08-14 |
| 869 | Bridging Solidity Evolution Gaps: An LLM-Enhanced Approach for Smart Contract Compilation Error Resolution Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This underscores the critical need for domain-specificadaptation in developing reliable LLM-based repair systems for smart contracts. Building upon these insights, we introduce SMCFIXER, a novel framework thatsystematically integrates expert knowledge retrieval with LLM-based repairmechanisms for Solidity compilation error resolution. |
Likai Ye; Mengliang Li; Dehai Zhao; Jiamou Sun; Xiaoxue Ren; | arxiv-cs.SE | 2025-08-14 |
| 870 | Performance of GPT-5 in Brain Tumor MRI Reasoning Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this study, we evaluated GPT-4o, GPT-5-nano, GPT-5-mini, andGPT-5 on a curated brain tumor VQA benchmark derived from 3 Brain TumorSegmentation (BraTS) datasets – glioblastoma (GLI), meningioma (MEN), and brainmetastases (MET). |
MOJTABA SAFARI et. al. | arxiv-cs.CV | 2025-08-14 |
| 871 | The GPT-4o Shock Emotional Attachment to AI Models and Its Impact on Regulatory Acceptance: A Cross-Cultural Analysis of The Immediate Transition from GPT-4o to GPT-5 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: In August 2025, a major AI company’s immediate, mandatory transition from itsprevious to its next-generation model triggered widespread public reactions. Icollected 150 posts in … |
Hiroki Naito; | arxiv-cs.CY | 2025-08-14 |
| 872 | Understanding Textual Emotion Through Emoji Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Using the TweetEval dataset, we address class imbalance through focalloss and regularization techniques. |
Ethan Gordon; Nishank Kuppa; Rigved Tummala; Sriram Anasuri; | arxiv-cs.CL | 2025-08-13 |
| 873 | Performance of GPT-5 Frontier Models in Ophthalmology Question Answering Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Cost-accuracy analysis identified several GPT-5 configurations on the Paretofrontier, with GPT-5-mini-low offering the most favorable low-cost,high-performance balance. These results benchmark GPT-5 on a high-qualityophthalmology dataset, demonstrate the influence of reasoning effort onaccuracy, and introduce an autograder framework for scalable evaluation ofLLM-generated answers against reference standards in ophthalmology. |
FARES ANTAKI et. al. | arxiv-cs.CL | 2025-08-13 |
| 874 | Echo-4o: Harnessing The Power of GPT-4o Synthetic Images for Improved Image Generation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Real-world data oftencontains complex background noise and inherent misalignment between textdescriptions and image content, whereas synthetic images offer pure backgroundsand long-tailed supervision signals, facilitating more accurate text-to-imagealignment. Building on these insights, we introduce Echo-4o-Image, a 180K-scalesynthetic dataset generated by GPT-4o, harnessing the power of synthetic imagedata to address blind spots in real-world coverage. |
JUNYAN YE et. al. | arxiv-cs.CV | 2025-08-13 |
| 875 | UWB at WASSA-2024 Shared Task 2: Cross-lingual Emotion Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents our system built for the WASSA-2024 Cross-lingual EmotionDetection Shared Task. |
Jakub Šmíd; Pavel Přibáň; Pavel Král; | arxiv-cs.CL | 2025-08-12 |
| 876 | Training-Free Text-Guided Color Editing with Multi-Modal Diffusion Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we presentColorCtrl, a training-free color editing method that leverages the attentionmechanisms of modern Multi-Modal Diffusion Transformers (MM-DiT). |
ZIXIN YIN et. al. | arxiv-cs.GR | 2025-08-12 |
| 877 | NEFMind: Parameter-Efficient Fine-Tuning of Open-Source LLMs for Telecom APIs Automation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The use of Service-Based Architecture in modern telecommunications hasexponentially increased Network Functions (NFs) and Application ProgrammingInterfaces (APIs), creating substantial operational complexities in servicediscovery and management. We introduce \textit{NEFMind}, a framework leveragingparameter-efficient fine-tuning of open-source Large Language Models (LLMs) toaddress these challenges. |
Zainab Khan; Ahmed Hussain; Mukesh Thakur; Arto Hellas; Panos Papadimitratos; | arxiv-cs.NI | 2025-08-12 |
| 878 | Capabilities of GPT-5 on Multimodal Medical Reasoning IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: A representative case study demonstrates GPT-5’s ability tointegrate visual and textual cues into a coherent diagnostic reasoning chain,recommending appropriate high-stakes interventions. |
Shansong Wang; Mingzhe Hu; Qiang Li; Mojtaba Safari; Xiaofeng Yang; | arxiv-cs.CL | 2025-08-11 |
| 879 | Bridging ASR and LLMs for Dysarthric Speech Recognition: Benchmarking Self-Supervised and Generative Approaches Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Speech Recognition (ASR) due to phoneme distortions and high variability.While self-supervised ASR models like Wav2Vec, HuBERT, and Whisper have shownpromise, their effectiveness in dysarthric speech remains unclear. This studysystematically benchmarks these models with different decoding strategies,including CTC, seq2seq, and LLM-enhanced decoding (BART,GPT-2, Vicuna). |
Ahmed Aboeitta; Ahmed Sharshar; Youssef Nafea; Shady Shehata; | arxiv-cs.SD | 2025-08-11 |
| 880 | What Am I Missing Here?: Evaluating Large Language Models for Masked Sentence Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We assess both fidelity (similarity to the originalsentence) and cohesiveness (fit within the surrounding context). |
Charlie Wyatt; Aditya Joshi; Flora Salim; | arxiv-cs.CL | 2025-08-11 |
| 881 | Training-Free ANN-to-SNN Conversion for High-Performance Spiking Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, existing methods still sufferfrom notable limitations, failing to effectively handle nonlinear operations inTransformer architectures and requiring additional fine-tuning processes forpre-trained ANNs. To address these issues, we propose a high-performance andtraining-free ANN-to-SNN conversion framework tailored for Transformerarchitectures. |
JINGYA WANG et. al. | arxiv-cs.LG | 2025-08-11 |
| 882 | GPT-2 As A Compression Preprocessor: Improving Gzip for Structured Text Domains Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, since gzip works on the principle of repetition of binarypatterns, one of the limitations of gzip is that domain-specific formats likeJSON, XML, HTML, and log files, while structured, may have semantic repetitionbut not syntactic repetition, which gzip finds difficult to compress. In thisarticle, we propose a GPT-based preprocessor for such domain-specific files. |
Anurag Kumar Ojha; | arxiv-cs.IR | 2025-08-10 |
| 883 | Arce: Augmented Roberta with Contextualized Elucidations for Ner in Automated Rule Checking Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Accurate information extraction from specialized texts is a criticalchallenge, particularly for named entity recognition (NER) in the architecture,engineering, and construction … |
Jian Chen; Jinbao Tian; Yankui Li; Yuqi Lu; Zhou Li; | arxiv-cs.CL | 2025-08-10 |
| 884 | AntiCheatPT: A Transformer-Based Approach to Cheat Detection in Competitive Computer Games Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Usingthis dataset, 90,707 context windows were created and subsequently augmented toaddress class imbalance. The transformer model, trained on these windows,achieved an accuracy of 89.17\% and an AUC of 93.36\% on an unaugmented testset. |
Mille Mei Zhen Loo; Gert Luzkov; Paolo Burelli; | arxiv-cs.AI | 2025-08-08 |
| 885 | Crisp Attention: Regularizing Transformers Via Structured Sparsity Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: While attention sparsity is widelystudied as a technique to improve computational efficiency, it is almostuniversally assumed to come at the cost of model accuracy. In this paper, wereport a surprising counter-example to this common wisdom. |
Sagar Gandhi; Vishal Gandhi; | arxiv-cs.CL | 2025-08-08 |
| 886 | LLMCARE: Alzheimer’s Detection Via Transformer Models Enhanced By LLM-Generated Synthetic Data Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The fusion model achieved F1 = 83.3 (AUC = 89.5), outperforming linguistic ortransformer-only baselines. |
ALI ZOLNOUR et. al. | arxiv-cs.CL | 2025-08-08 |
| 887 | Gpt-oss-120b & Gpt-oss-20b Model Card Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: We present gpt-oss-120b and gpt-oss-20b, two open-weight reasoning models that push the frontier of accuracy and inference cost. The models use an efficient mixture-of-expert … |
OPENAI SANDHINI AGARWAL et. al. | ArXiv | 2025-08-08 |
| 888 | H-Net++: Hierarchical Dynamic Chunking for Tokenizer-Free Language Modelling in Morphologically-Rich Languages Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose H-NET++, a hierarchical dynamic-chunking model thatlearns linguistically-informed segmentation through end-to-end training. |
Mehrdad Zakershahrak; Samira Ghodratnama; | arxiv-cs.CL | 2025-08-07 |
| 889 | Streamlining Admission with LOR Insights: AI-Based Leadership Assessment in Online Master’s Program Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However,reviewing these text-heavy materials is time-consuming and labor-intensive. Toaddress this challenge and support the admission committee in providingfeedback for students’ professional growth, our study introduces LORI: LORInsights, a novel AI-based detection tool for assessing leadership skills inLORs submitted by online master’s program applicants. |
MERYEM YILMAZ SOYLU et. al. | arxiv-cs.AI | 2025-08-07 |
| 890 | Leveraging Large Language Models for SQL Behavior-based Database Intrusion Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper introduces a two-tiered anomaly detection approach forStructured Query Language (SQL) using the Bidirectional Encoder Representationsfrom Transformers (BERT) model, specifically DistilBERT, a more efficient,pre-trained version. |
MEITAL SHLEZINGER et. al. | arxiv-cs.CR | 2025-08-06 |
| 891 | Advancing Hate Speech Detection with Transformers: Insights from The MetaHate Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We evaluate multiple state-of-the-arttransformer models, including BERT, RoBERTa, GPT-2, and ELECTRA, withfine-tuned ELECTRA achieving the highest performance (F1 score: 0.8980). |
Santosh Chapagain; Shah Muhammad Hamdi; Soukaina Filali Boubrahimi; | arxiv-cs.LG | 2025-08-06 |
| 892 | Improving Crash Data Quality with Large Language Models: Evidence from Secondary Crash Narratives in Kentucky Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study evaluates advanced natural language processing (NLP) techniques toenhance crash data quality by mining crash narratives, using secondary crashidentification in Kentucky as a case study. |
Xu Zhang; Mei Chen; | arxiv-cs.CL | 2025-08-06 |
| 893 | Compressing Large Language Models with PCA Without Performance Loss Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We demonstrate that Principal Component Analysis (PCA), when applied in astructured manner, either to polar-transformed images or segment-wise to tokensequences, enables extreme compression of neural models without sacrificingperformance. |
Magnus Bengtsson; | arxiv-cs.CE | 2025-08-06 |
| 894 | Machine Learning-Based Vulnerability Detection in Rust Code Using LLVM IR and Transformer Model Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Rust’s growing popularity in high-integrity systems requires automated vulnerability detection in order to maintain its strong safety guarantees. Although Rust’s ownership model … |
Young Lee; Syeda Jannatul Boshra; Jeong Yang; Zechun Cao; Gongbo Liang; | Mach. Learn. Knowl. Extr. | 2025-08-06 |
| 895 | A Reproducible, Scalable Pipeline for Synthesizing Autoregressive Model Literature Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The accelerating pace of research on autoregressive generative models hasproduced thousands of papers, making manual literature surveys and reproductionstudies increasingly impractical. We present a fully open-source, reproduciblepipeline that automatically retrieves candidate documents from publicrepositories, filters them for relevance, extracts metadata, hyper-parametersand reported results, clusters topics, produces retrieval-augmented summariesand generates containerised scripts for re-running selected experiments.Quantitative evaluation on 50 manually-annotated papers shows F1 scores above0.85 for relevance classification, hyper-parameter extraction and citationidentification. |
Faruk Alpay; Bugra Kilictas; Hamdi Alakkad; | arxiv-cs.IR | 2025-08-06 |
| 896 | Lightweight Transformers for Zero-Shot and Fine-Tuned Text-to-SQL Generation Using Spider Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study evaluates three lightweight transformer models -T5-Small, BART-Small, and GPT-2 – on the Spider dataset, focusing onlow-resource settings. |
Chirag Seth; Utkarsh Singh; | arxiv-cs.CL | 2025-08-06 |
| 897 | Can Large Language Models Bridge The Gap in Environmental Knowledge? Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This research investigates the potential of Artificial Intelligence (AI)models to bridge the knowledge gap in environmental education among universitystudents. |
Linda Smail; David Santandreu Calonge; Firuz Kamalov; Nur H. Orak; | arxiv-cs.AI | 2025-08-05 |
| 898 | Estimating Worst-Case Frontier Risks of Open-Weight LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we study the worst-case frontier risks of releasing gpt-oss. |
Eric Wallace; Olivia Watkins; Miles Wang; Kai Chen; Chris Koch; | arxiv-cs.LG | 2025-08-05 |
| 899 | GP and LLMs for Program Synthesis: No Clear Winners Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we compared the ability of PushGP andGPT-4o to synthesize computer programs for tasks from the PSB2 benchmark suite.We used three prompt variants with GPT-4o: input-output examples (data-only),textual description of the task (text-only), and a combination of both textualdescriptions and input-output examples (data-text). |
Jose Guadalupe Hernandez; Anil Kumar Saini; Gabriel Ketron; Jason H. Moore; | arxiv-cs.NE | 2025-08-05 |
| 900 | R2GenKG: Hierarchical Multi-modal Knowledge Graph for LLM-based Radiology Report Generation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: X-ray medical report generation is one of the important applications ofartificial intelligence in healthcare. With the support of large foundationmodels, the quality of medical … |
FUTIAN WANG et. al. | arxiv-cs.CV | 2025-08-05 |
| 901 | From Text to Trajectories: GPT-2 As An ODE Solver Via In-Context Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To shed light on its underlyingmechanisms, this paper investigates whether LLMs can solve ordinarydifferential equations (ODEs) under the ICL setting. We formulate standard ODEproblems and their solutions as sequential prompts and evaluate GPT-2 models onthese tasks. |
Ziyang Ma; Baojian Zhou; Deqing Yang; Yanghua Xiao; | arxiv-cs.AI | 2025-08-04 |
| 902 | Contextual Graph Transformer: A Small Language Model for Enhanced Engineering Document Information Extraction Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Standard transformer-based language models, while powerful for general text,often struggle with the fine-grained syntax and entity relationships in complextechnical, engineering documents. To address this, we propose the ContextualGraph Transformer (CGT), a hybrid neural architecture that combines GraphNeural Networks (GNNs) and Transformers for domain-specific question answering.CGT constructs a dynamic graph over input tokens using sequential, skip-gram,and semantic similarity edges, which is processed by GATv2Conv layers for localstructure learning. |
Karan Reddy; Mayukha Pal; | arxiv-cs.CL | 2025-08-04 |
| 903 | Urban In-Context Learning: Bridging Pretraining and Inference Through Masked Diffusion for Urban Profiling Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we propose Urban In-Context Learning,a framework that unifies pretraining and inference via a masked autoencodingprocess over urban regions. |
Ruixing Zhang; Bo Wang; Tongyu Zhu; Leilei Sun; Weifeng Lv; | arxiv-cs.LG | 2025-08-04 |
| 904 | Interference Matrix: Quantifying Cross-Lingual Interference in Transformer Encoders Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we present a comprehensive study of language interference inencoder-only Transformer models across 83 languages. |
BELEN ALASTRUEY et. al. | arxiv-cs.CL | 2025-08-04 |
| 905 | An Explainable Method for Access Control Policies Classification Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Access control is one of the most fundamental components used in information security frameworks. However, as organizations increasingly rely on digital systems to manage … |
Luca Petrillo; Fabio Martinelli; Antonella Santone; F. Mercaldo; | 2025 IEEE International Conference on Cyber Security and … | 2025-08-04 |
| 906 | IReflect: Automated Playtesting Feedback with Knowledge Graph-Augmented GPT-4 for Creative Media Courses Related Papers Related Patents Related Grants Related Venues Related Experts View Save |
Koh Tee Sing Newton; Wenli Yu; Bhojan Anand; | Proceedings of the 2025 ACM Conference on International … | 2025-08-02 |
| 907 | VAULT: Vigilant Adversarial Updates Via LLM-Driven Retrieval-Augmented Generation for NLI Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: We introduce VAULT, a fully automated adversarial RAG pipeline that systematically uncovers and remedies weaknesses in NLI models through three stages: retrieval, adversarial … |
Roie Kazoom; Ofir Cohen; Rami Puzis; A. Shabtai; O. Hadar; | ArXiv | 2025-08-01 |
| 908 | Automated Type Annotation in Python Using Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, weexplore the use of LLMs for generating type annotations in Python. |
Varun Bharti; Shashwat Jha; Dhruv Kumar; Pankaj Jalote; | arxiv-cs.PL | 2025-08-01 |
| 909 | Cross-Domain Web Information Extraction at Pinterest Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we present Pinterest’s system forattribute extraction, which achieves remarkable accuracy and scalability at amanageable cost. |
MICHAEL FARAG et. al. | arxiv-cs.CL | 2025-08-01 |
| 910 | TCAC-transformer: A Fast Convolutional Transformer with Temporal-channel Attention for Efficient Industrial Fault Diagnosis Related Papers Related Patents Related Grants Related Venues Related Experts View Save |
WEI WU et. al. | Expert Syst. Appl. | 2025-08-01 |
| 911 | HateFusion: Harnessing Attention-Based Techniques for Enhanced Filtering and Detection of Implicit Hate Speech Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Hate speech is a complex, multifaceted form of harmful material that targets individuals or groups. Detecting implicit hate speech poses a significant challenge due to its subtle … |
Ashok Yadav; Vrijendra Singh; | IEEE Transactions on Computational Social Systems | 2025-08-01 |
| 912 | What’s Taboo for You? – An Empirical Evaluation of LLMs Behavior Toward Sensitive Content Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Proprietary Large Language Models (LLMs) have shown tendencies towardpoliteness, formality, and implicit content moderation. |
ALFIO FERRARA et. al. | arxiv-cs.CL | 2025-07-31 |
| 913 | Hybrid LSTM-Transformer Models for Profiling Highway-Railway Grade Crossings Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Hump crossings, or high-profile Highway Railway Grade Crossings (HRGCs), pose safety risks to highway vehicles due to potential hang-ups. These crossings typically result from … |
KAUSTAV CHATTERJEE et. al. | ArXiv | 2025-07-31 |
| 914 | Short-term Cryptocurrency Price Forecasting Based on News Headline Analysis Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: This article presents a method for short-term cryptocurrency price forecasting utilizing news headlines.The study analyzes the impact of news on asset prices within one hour of … |
Vladimir Dikovitsky; | Frontiers Blockchain | 2025-07-30 |
| 915 | Context-aware Rotary Position Embedding Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we propose CARoPE (Context-Aware Rotary PositionalEmbedding), a novel generalization of RoPE that dynamically generateshead-specific frequency patterns conditioned on token embeddings. |
Ali Veisi; Delaram Fartoot; Hamidreza Amirzadeh; | arxiv-cs.CL | 2025-07-30 |
| 916 | Enabling Few-Shot Alzheimer’s Disease Diagnosis on Biomarker Data with Tabular LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose anovel framework called TAP-GPT, Tabular Alzheimer’s Prediction GPT, that adaptsTableGPT2, a multimodal tabular-specialized LLM originally developed forbusiness intelligence tasks, for AD diagnosis using structured biomarker datawith small sample sizes. |
SOPHIE KEARNEY et. al. | arxiv-cs.CL | 2025-07-30 |
| 917 | Automatic Classification of User Requirements from Online Feedback — A Replication Study Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Natural language processing (NLP) techniques have been widely applied in therequirements engineering (RE) field to support tasks such as classification andambiguity detection. |
MEET BHATT et. al. | arxiv-cs.CL | 2025-07-29 |
| 918 | Modelling Adjectival Modification Effects on Semantic Plausibility Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we tackle theADEPT challenge benchmark [6] consisting of 16K English sentence pairsdiffering by exactly one adjectival modifier. |
Anna Golub; Beate Zywietz; Annerose Eichel; | arxiv-cs.CL | 2025-07-29 |
| 919 | Large Language Model-Based Framework for Explainable Cyberattack Detection in Automatic Generation Control Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper proposes a hybrid framework thatintegrates lightweight ML-based attack detection with natural languageexplanations generated by Large Language Models (LLMs). |
MUHAMMAD SHARSHAR et. al. | arxiv-cs.CR | 2025-07-29 |
| 920 | LLM-based Content Classification Approach for GitHub Repositories By The README Files Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this study, an approachis developed to fine-tune LLMs for automatically classifying different sectionsof GitHub README files. |
Malik Uzair Mehmood; Shahid Hussain; Wen Li Wang; Muhammad Usama Malik; | arxiv-cs.AI | 2025-07-29 |
| 921 | Unified Transformer Framework for Automated Cyberbullying Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Cyberbullying is a fast-growing public-health hazard, demanding reliable, real-time detection of abusive language online. This study presents a unified transformer framework that … |
ENAS A. ALIKHASHASHNEH et. al. | Int. J. Cloud Appl. Comput. | 2025-07-29 |
| 922 | FHSTP@EXIST 2025 Benchmark: Sexism Detection with Transparent Speech Concept Bottleneck Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we describe oursolutions and report results for three subtasks: Subtask 1.1 – SexismIdentification in Tweets, Subtask 1.2 – Source Intention in Tweets, and Subtask1.3 – Sexism Categorization in Tweets. |
ROBERTO LABADIE-TAMAYO et. al. | arxiv-cs.CL | 2025-07-28 |
| 923 | Enhancing Chatbot Responses Through Improved T5 Model Incorporating Aggregated Multi-Head Attention Mechanism and Bidirectional Long Short-Term Memory Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Artificial Intelligence (AI) chatbots have become indispensable for natural language interaction, with transformer-based models driving advances in conversational agent (CA) … |
M. N.; V. A.; | J. Univers. Comput. Sci. | 2025-07-28 |
| 924 | Understanding Public Perception of Crime in Bangladesh: A Transformer-Based Approach with Explainability Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose a transformer-basedmodel utilizing the XLM-RoBERTa Base architecture, which achieves aclassification accuracy of 97%, outperforming existing state-of-the-art methodsin Bangla sentiment analysis. |
FATEMA BINTE HASSAN et. al. | arxiv-cs.CL | 2025-07-28 |
| 925 | GPT-IMAGE-EDIT-1.5M: A Million-Scale, GPT-Generated Image Dataset IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To bridge this gap, we introduceGPT-IMAGE-EDIT-1.5M, a publicly available, large-scale image-editing corpuscontaining more than 1.5 million high-quality triplets (instruction, sourceimage, edited image). We systematically construct this dataset by leveragingthe versatile capabilities of GPT-4o to unify and refine three popularimage-editing datasets: OmniEdit, HQ-Edit, and UltraEdit. |
YUHAN WANG et. al. | arxiv-cs.CV | 2025-07-28 |
| 926 | L-MCAT: Unpaired Multimodal Transformer with Contrastive Attention for Label-Efficient Satellite Image Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose the Lightweight Multimodal Contrastive Attention Transformer(L-MCAT), a novel transformer-based framework for label-efficient remotesensing image classification using unpaired multimodal satellite data. |
Mitul Goswami; Mrinal Goswami; | arxiv-cs.CV | 2025-07-27 |
| 927 | Leveraging Fine-Tuned Large Language Models for Interpretable Pancreatic Cystic Lesion Feature Extraction and Risk Categorization Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Radiologist inter-reader agreement washigh (Fleiss’ Kappa = 0.888) and showed no statistically significant differencewith the addition of DeepSeek-FT-CoT (Fleiss’ Kappa = 0.893) or GPT-CoT(Fleiss’ Kappa = 0.897), indicating that both models achieved agreement levelson par with radiologists. |
EBRAHIM RASROMANI et. al. | arxiv-cs.AI | 2025-07-26 |
| 928 | The Carbon Cost of Conversation, Sustainability in The Age of Language Models Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Large language models (LLMs) like GPT-3 and BERT have revolutionized naturallanguage processing (NLP), yet their environmental costs remain dangerouslyoverlooked. This article … |
SAYED MAHBUB HASAN AMIRI et. al. | arxiv-cs.CY | 2025-07-26 |
| 929 | ReCatcher: Towards LLMs Regression Testing for Code Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, such updates canintroduce regressions, not only in correctness but also in code quality andperformance. To address this, we present ReCatcher, a regression testingframework for Python code generation. |
Altaf Allah Abbassi; Leuson Da Silva; Amin Nikanjam; Foutse Khomh; | arxiv-cs.SE | 2025-07-25 |
| 930 | Learning Neuro-symbolic Convergent Term Rewriting Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Building neural systems that can learn to execute symbolic algorithms is achallenging open problem in artificial intelligence, especially when aiming forstrong generalization and out-of-distribution performance. In this work, weintroduce a general framework for learning convergent term rewriting systemsusing a neuro-symbolic architecture inspired by the rewriting algorithm itself.We present two modular implementations of such architecture: the NeuralRewriting System (NRS) and the Fast Neural Rewriting System (FastNRS). |
Flavio Petruzzellis; Alberto Testolin; Alessandro Sperduti; | arxiv-cs.AI | 2025-07-25 |
| 931 | Iwin Transformer: Hierarchical Vision Transformer Using Interleaved Windows Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce Iwin Transformer, a novel position-embedding-free hierarchicalvision transformer, which can be fine-tuned directly from low to highresolution, through the collaboration of innovative interleaved windowattention and depthwise separable convolution. |
Simin Huo; Ning Li; | arxiv-cs.CV | 2025-07-24 |
| 932 | Restoring Rhythm: Punctuation Restoration Using Transformer Models for Bangla, A Low-Resource Language Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this study, we explore the applicationof transformer-based models, specifically XLM-RoBERTa-large, to automaticallyrestore punctuation in unpunctuated Bangla text. |
Md Obyedullahil Mamun; Md Adyelullahil Mamun; Arif Ahmad; Md. Imran Hossain Emu; | arxiv-cs.CL | 2025-07-24 |
| 933 | The Role of Orthographic Consistency in Multilingual Embedding Models for Text Classification in Arabic-Script Languages Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce the Arabic Script RoBERTa (AS-RoBERTa) family:four RoBERTa-based models, each pre-trained on a large corpus tailored to itsspecific language. |
ABDULHADY ABAS ABDULLAH et. al. | arxiv-cs.CL | 2025-07-24 |
| 934 | Large Language Model-Based Topic-Level Sentiment Analysis for E-Grocery Consumer Reviews Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Customer sentiment analysis plays a pivotal role in the digital economy by offering comprehensive insights that inform strategic business decisions, optimize digital marketing … |
JULIZAR ISYA PANDU WANGSA et. al. | Big Data Cogn. Comput. | 2025-07-23 |
| 935 | DNT: A Deeply Normalized Transformer That Can Be Trained By Momentum SGD Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Previous works show thatit is mainly due to a heavy-tailed distribution of the gradients. In thispaper, we introduce a Deeply Normalized Transformer (DNT), which ismeticulously engineered to overcome this limitation enabling seamless trainingwith vanilla mSGDW while yielding comparable performance to the Transformerstrained via AdamW. |
XIANBIAO QI et. al. | arxiv-cs.LG | 2025-07-23 |
| 936 | Technical Report of TeleChat2, TeleChat2.5 and T1 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce the latest series of TeleChat models: \textbf{TeleChat2},\textbf{TeleChat2.5}, and \textbf{T1}, offering a significant upgrade overtheir predecessor, TeleChat. |
ZIHAN WANG et. al. | arxiv-cs.CL | 2025-07-23 |
| 937 | Can LLMs Write CI? A Study on Automatic Generation of GitHub Actions Configurations Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents a preliminary studyevaluating six LLMs for generating GitHub Actions configurations from naturallanguage descriptions. |
Taher A. Ghaleb; Dulina Rathnayake; | arxiv-cs.SE | 2025-07-22 |
| 938 | Write, Rank, or Rate: Comparing Methods for Studying Visualization Affordances Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To supplement this work, we present a case study with GPT-4o,exploring the use of large language models (LLMs) to elicit human-like chartinterpretations. |
Chase Stokes; Kylie Lin; Cindy Xiong Bearfield; | arxiv-cs.HC | 2025-07-22 |
| 939 | Multi-Label Classification with Generative AI Models in Healthcare: A Case Study of Suicidality and Risk Factors Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present a novel end toend generative MLC pipeline and introduce advanced evaluation methods,including label set level metrics and a multilabel confusion matrix for erroranalysis. |
MING HUANG et. al. | arxiv-cs.CL | 2025-07-22 |
| 940 | Causal Graph Fuzzy LLMs: A First Introduction and Applications in Time Series Forecasting Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In recent years, the application of Large Language Models (LLMs) to timeseries forecasting (TSF) has garnered significant attention among researchers.This study presents a new frame of LLMs named CGF-LLM using GPT-2 combined withfuzzy time series (FTS) and causal graph to predict multivariate time series,marking the first such architecture in the literature. |
OMID ORANG et. al. | arxiv-cs.LG | 2025-07-22 |
| 941 | Dutch CrowS-Pairs: Adapting A Challenge Dataset for Measuring Social Biases in Language Models for Dutch Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Using the Dutch CrowS-Pairs dataset, we show thatvarious language models, BERTje, RobBERT, multilingual BERT, GEITje andMistral-7B exhibit substantial bias across the various bias categories. |
Elza Strazda; Gerasimos Spanakis; | arxiv-cs.CL | 2025-07-22 |
| 942 | Confidence Optimization for Probabilistic Encoding Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The method we proposed ismodel-agnostic, and extensive experiments on natural language classificationtasks demonstrate that our method significantly improves performance andgeneralization on both the BERT and the RoBERTa model. |
Pengjiu Xia; Yidian Huang; Wenchao Wei; Yuwen Tan; | arxiv-cs.LG | 2025-07-22 |
| 943 | Probing Information Distribution in Transformer Architectures Through Entropy Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This work explores entropy analysis as a tool for probing informationdistribution within Transformer-based architectures. By quantifying token-leveluncertainty and examining entropy patterns across different stages ofprocessing, we aim to investigate how information is managed and transformedwithin these models. |
Amedeo Buonanno; Alessandro Rivetti; Francesco A. N. Palmieri; Giovanni Di Gennaro; Gianmarco Romano; | arxiv-cs.CL | 2025-07-21 |
| 944 | The Lawyer That Never Thinks: Consistency and Fairness As Keys to Reliable AI Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Large Language Models (LLMs) are increasingly used in high-stakes domains like law and research, yet their inconsistencies and response instability raise concerns about trustworthiness. |
Dana R Alsagheer; Abdulrahman Kamal; Mohammad Kamal; Cosmo Yang Wu; Weidong Shi; | acl | 2025-07-21 |
| 945 | Mining The Uncertainty Patterns of Humans and Models in The Annotation of Moral Foundations and Human Values Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper makes a further step by investigating the relationship between HLV and model uncertainty, and the impact of linguistic features of the items on both. |
Neele Falk; Gabriella Lapesa; | acl | 2025-07-21 |
| 946 | EdgeInfinite: A Memory-Efficient Infinite-Context Transformer for Edge Devices Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present EdgeInfinite, a memory-efficient solution for infinite contexts that integrates compressed memory into Transformer-based LLMs through a trainable memory-gating module. |
JIYU CHEN et. al. | acl | 2025-07-21 |
| 947 | FoldMoE: Efficient Long Sequence MoE Training Via Attention-MoE Pipelining Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present FoldMoE, a high-performance MoE training system that enables token-level overlapping across entire Transformer blocks through novel attention-MoE pipelining. |
GUICHAO ZHU et. al. | acl | 2025-07-21 |
| 948 | Enhancing Hindi NER in Low Context: A Comparative Study of Transformer-based Models with Vs. Without Retrieval Augmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study adds significant knowledge abouthow best to use data augmentation methods and pretrained models to enhance NERperformance, particularly in languages with limited resources. |
Sumit Singh; Rohit Mishra; Uma Shanker Tiwary; | arxiv-cs.CL | 2025-07-21 |
| 949 | Weak Links in LinkedIn: Enhancing Fake Profile Detection in The Age of LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this study, we evaluate the robustness ofexisting detectors against LLM-generated profiles. |
Apoorva Gulati; Rajesh Kumar; Vinti Agarwal; Aditya Sharma; | arxiv-cs.SI | 2025-07-21 |
| 950 | Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference IF:6 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: In this paper, we introduce ModernBERT, bringing modern model optimizations to encoder-only models and representing a major Pareto improvement over older encoders. |
BENJAMIN WARNER et. al. | acl | 2025-07-21 |
| 951 | When GPT Spills The Tea: Comprehensive Assessment of Knowledge File Leakage in GPTs Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we present a comprehensive risk assessment of knowledge file leakage, leveraging a novel workflow inspired by Data Security Posture Management (DSPM). |
Xinyue Shen; Yun Shen; Michael Backes; Yang Zhang; | acl | 2025-07-21 |
| 952 | Segment-Based Attention Masking for GPTs Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: In this work, attention is masked based on the known block structure at the prefill phase, followed by the conventional token-by-token autoregressive process after that. |
Shahar Katz; Liran Ringel; Yaniv Romano; Lior Wolf; | acl | 2025-07-21 |
| 953 | Enhancing Goal-oriented Proactive Dialogue Systems Via Consistency Reflection and Correction Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, previous research has focused predominantly on optimizing these paths while neglecting the inconsistencies that may arise between generated responses and dialogue contexts, including user profiles, dialogue history, domain knowledge, and subgoals. To address this issue, we introduce a model-agnostic two-stage Consistency Reflection and Correction (CRC) framework. |
Didi Zhang; Yaxin Fan; Peifeng Li; Qiaoming Zhu; | acl | 2025-07-21 |
| 954 | EVOLVE-X: Embedding Fusion and Language Prompting for User Evolution Forecasting on Social Media Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this study, we present a novel approach that leveragesopen-source models Llama-3-Instruct, Mistral-7B-Instruct, Gemma-7B-IT throughprompt engineering, combined with GPT-2, BERT, and RoBERTa using a jointembedding technique, to analyze and predict the evolution of user behavior onsocial media over their lifetime. |
Ismail Hossain; Sai Puppala; Md Jahangir Alam; Sajedul Talukder; | arxiv-cs.SI | 2025-07-21 |
| 955 | Powerformer: Efficient and High-Accuracy Privacy-Preserving Language Model with Homomorphic Encryption Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose Powerformer, an efficient homomorphic encryption (HE)-based privacy-preserving language model (PPLM) designed to reduce computation overhead while maintaining model performance. |
Dongjin Park; Eunsang Lee; Joon-Woo Lee; | acl | 2025-07-21 |
| 956 | Automatic Evaluation for Text-to-image Generation: Task-decomposed Framework, Distilled Training, and Meta-evaluation Benchmark IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: In contrast, while open-source MLLMs demonstrate promising skills in vision and language understanding, they underperform in comprehensive image quality assessment. To address these challenges, we propose a task decomposition evaluation framework based on GPT-4o to automatically construct a specialized training dataset, breaking down the multifaceted evaluation process into simpler sub-tasks and thus reducing learning complexity. |
RONG-CHENG TU et. al. | acl | 2025-07-21 |
| 957 | Principled Understanding of Generalization for Generative Transformer Models in Arithmetic Reasoning Tasks Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper develops a unified theoretical framework for understanding the generalization behaviors of transformers in arithmetic tasks, focusing on length generalization. |
Xingcheng Xu; Zibo Zhao; Haipeng Zhang; Yanqing Yang; | acl | 2025-07-21 |
| 958 | INJONGO: A Multicultural Intent Detection and Slot-filling Dataset for 16 African Languages Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we introduce “INJONGO” – a multicultural, open-source benchmark dataset for 16 African languages with utterances generated by native speakers across diverse domains, including banking, travel, home, and dining. |
HAO YU et. al. | acl | 2025-07-21 |
| 959 | GPT-4 As A Homework Tutor Can Improve Student Engagement and Learning Outcomes IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This work contributes to the scarce empirical literature on LLM-based interactive homework in real-world educational settings and offers a practical, scalable solution to improve homework in schools. |
Alessandro Vanzo; Sankalan Pal Chowdhury; Mrinmaya Sachan; | acl | 2025-07-21 |
| 960 | OmniFlatten: An End-to-end GPT Model for Seamless Voice Conversation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: In this paper, we introduce a novel End-to-End GPT-based model OmniFlatten for full-duplex conversation, capable of effectively modeling the complex behaviors inherent to natural conversations with low latency. |
QINGLIN ZHANG et. al. | acl | 2025-07-21 |
| 961 | Efficient OpAmp Adaptation for Zoom Attention to Golden Contexts Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Recent work proposes the differential attention mechanism to address this issue, but this mechanism is limited by an unsuitable common-mode rejection ratio (CMRR) and high computational costs. Inspired by the operational amplifier (OpAmp), we propose the OpAmp adaptation to address these challenges, which is implemented with adapters efficiently. |
Haoyuan Wu; Rui Ming; Haisheng Zheng; Zhuolun He; Bei Yu; | acl | 2025-07-21 |
| 962 | PaSa: An LLM Agent for Comprehensive Academic Paper Search IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: We introduce PaSa, an advanced Paper Search agent powered by large language models. |
YICHEN HE et. al. | acl | 2025-07-21 |
| 963 | A Hybrid Semantic and Multi-Attention Mechanism Approach for Detecting Vulnerabilities in Smart Contract Code Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Driven by blockchain technology, numerous industries are increasingly adopting smart contracts to enhance efficiency, reduce costs, and improve transparency. As a result, ensuring … |
Zhenxiang He; Yanlin Liu; Xiaohui Sun; | Symmetry | 2025-07-21 |
| 964 | Inner Thinking Transformer: Leveraging Dynamic Depth Scaling to Foster Adaptive Internal Thinking IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Empirical analysis reveals challenging tokens induce abrupt gradient spikes across layers, exposing architectural stress points in standard Transformers. Building on this insight, we propose Inner Thinking Transformer (ITT), which reimagines layer computations as implicit thinking steps. |
YILONG CHEN et. al. | acl | 2025-07-21 |
| 965 | Can Uniform Meaning Representation Help GPT-4 Translate from Indigenous Languages? Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we explore the downstream utility of UMR for low-resource languages by incorporating it into GPT-4 prompts. |
Shira Wein; | acl | 2025-07-21 |
| 966 | Language Models for Controllable DNA Sequence Design Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we introduce ATGC-Gen, an Automated TransformerGenerator for Controllable Generation, which leverages cross-modal encoding tointegrate diverse biological signals. |
XINGYU SU et. al. | arxiv-cs.LG | 2025-07-19 |
| 967 | XL-DURel: Finetuning Sentence Transformers for Ordinal Word-in-Context Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose XL-DURel, a finetuned, multilingual Sentence Transformer modeloptimized for ordinal Word-in-Context classification. |
Sachin Yadav; Dominik Schlechtweg; | arxiv-cs.CL | 2025-07-19 |
| 968 | InTraVisTo: Inside Transformer Visualisation Tool Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we introduce a new tool,InTraVisTo (Inside Transformer Visualisation Tool), designed to enableresearchers to investigate and trace the computational process that generateseach token in a Transformer-based LLM. |
Nicolò Brunello; Davide Rigamonti; Andrea Sassella; Vincenzo Scotti; Mark James Carman; | arxiv-cs.CL | 2025-07-18 |
| 969 | AI-Assisted Fixes to Code Review Comments at Scale Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: As a baseline, we compare GPT-4o to our small and largeLlama models. |
CHANDRA MADDILA et. al. | arxiv-cs.SE | 2025-07-17 |
| 970 | Compact Vision Transformer By Reduction of Kernel Complexity Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we introduce Transformerwith Kernel Complexity Reduction, or KCR-Transformer, a compact transformerblock equipped with differentiable channel selection, guided by a novel andsharp theoretical generalization bound. |
Yancheng Wang; Yingzhen Yang; | arxiv-cs.CV | 2025-07-17 |
| 971 | Beyond Architectures: Evaluating The Role of Contextual Embeddings in Detecting Bipolar Disorder on Social Media Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper explores the advancednatural language processing (NLP) models for recognizing signs of bipolardisorder based on user-generated social media text. |
Khalid Hasan; Jamil Saquer; | arxiv-cs.CL | 2025-07-17 |
| 972 | PRISM: Distributed Inference for Foundation Models at Edge Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we propose PRISM, acommunication-efficient and compute-aware strategy for distributed Transformerinference on edge devices. |
Muhammad Azlan Qazi; Alexandros Iosifidis; Qi Zhang; | arxiv-cs.LG | 2025-07-16 |
| 973 | ROSE: Transformer-Based Refactoring Recommendation for Architectural Smells Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We frame the task as a three-classclassification problem and fine-tune both models on over 2 million refactoringinstances mined from 11,149 open-source Java projects. |
Samal Nursapa; Anastassiya Samuilova; Alessio Bucaioni; Phuong T. Nguyen; | arxiv-cs.SE | 2025-07-16 |
| 974 | Mitigating Trojanized Prompt Chains in Educational LLM Use Cases: Experimental Findings and Detection Tool Design Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study explores howstudents may Trojanize prompts to elicit unsafe or unintended outputs fromLLMs, bypassing established content moderation systems with safety guardrils.Through a systematic experiment involving simulated K–12 queries andmulti-turn dialogues, we expose key vulnerabilities in GPT-3.5 and GPT-4. |
Richard M. Charles; James H. Curry; Richard B. Charles; | arxiv-cs.CR | 2025-07-15 |
| 975 | Cross-lingual Few-shot Learning for Persian Sentiment Analysis with Incremental Adaptation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This research examines cross-lingual sentiment analysis using few-shotlearning and incremental learning methods in Persian. |
Farideh Majidi; Ziaeddin Beheshtifard; | arxiv-cs.CL | 2025-07-15 |
| 976 | Addressing Data Imbalance in Transformer-Based Multi-Label Emotion Detection with Weighted Loss Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper explores the application of a simple weighted loss function toTransformer-based models for multi-label emotion detection in SemEval-2025Shared Task 11. |
Xia Cui; | arxiv-cs.CL | 2025-07-15 |
| 977 | Based on BERT-GPT-GNN Converged Architecture: Intelligent Generation Engine for Complex SQL Queries in Business Intelligence Related Papers Related Patents Related Grants Related Venues Related Experts View Save |
Shiwei Chu; Jie Liu; | Discover Artificial Intelligence | 2025-07-15 |
| 978 | Social Media Sentiments Analysis on The July Revolution in Bangladesh: A Hybrid Transformer Based Machine Learning Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Inthis study, we present a hybrid transformer-based sentiment analysis frameworkto decode public opinion expressed in social media comments during and afterthe revolution. |
Md. Sabbir Hossen; Md. Saiduzzaman; Pabon Shaha; | arxiv-cs.CL | 2025-07-15 |
| 979 | From BERT to Qwen: Hate Detection Across Architectures Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Online platforms struggle to curb hate speech without over-censoringlegitimate discourse. Early bidirectional transformer encoders made bigstrides, but the arrival of ultra-large … |
Ariadna Mon; Saúl Fenollosa; Jon Lecumberri; | arxiv-cs.CL | 2025-07-14 |
| 980 | Player-Team Heterogeneous Interaction Graph Transformer for Soccer Outcome Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: While it conventionally relies on meticulous feature engineering, deeplearning techniques have recently shown a great promise in learning effectiveplayer and team representations directly for soccer outcome prediction.However, existing methods often overlook the heterogeneous nature ofinteractions among players and teams, which is crucial for accurately modelingmatch dynamics. To address this gap, we propose HIGFormer (HeterogeneousInteraction Graph Transformer), a novel graph-augmented transformer-based deeplearning model for soccer outcome prediction. |
Lintao Wang; Shiwen Xu; Michael Horton; Joachim Gudmundsson; Zhiyong Wang; | arxiv-cs.LG | 2025-07-14 |
| 981 | Language Models for Adult Service Website Text Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Wedemonstrate the use of our best-performing custom configuration on three tasksrelated to ASW data analysis: (i) decomposing the giant component in a graphrepresentation of ASW data, (ii) clustering ASW ad text, and (iii) using thelearned token embeddings to understand the use of emojis in the illicit contextwe study. |
Nickolas Freeman; Thanh Nguyen; Gregory Bott; Jason Parton; Collin Francel; | arxiv-cs.CL | 2025-07-14 |
| 982 | Pimba: A Processing-in-Memory Acceleration for Post-Transformer Large Language Model Serving Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This shift presents a key challenge: building a servingsystem that efficiently supports both transformer and post-transformer LLMswithin a unified framework. To address this challenge, we analyze theperformance characteristics of transformer and post-transformer LLMs. |
WONUNG KIM et. al. | arxiv-cs.AR | 2025-07-14 |
| 983 | Assessing Support for The TREC 2024 RAG Track: A Large-Scale Comparative Study of LLM and Human Evaluations Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We conducted a comparative study of submissions to the TREC 2024 RAG Track, evaluating an automatic LLM judge (GPT-4o) against human judges for support assessment. |
NANDAN THAKUR et. al. | sigir | 2025-07-13 |
| 984 | WebFAQ: A Multilingual Collection of Natural Q&A Datasets for Dense Retrieval Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present WebFAQ, a large-scale collection of open-domain question answering datasets derived from FAQ-style schema.org annotations. |
Michael Dinzinger; Laura Caspari; Kanishka Ghosh Dastidar; Jelena Mitrovi\'{c}; Michael Granitzer; | sigir | 2025-07-13 |
| 985 | R2LLMs: Retrieval and Ranking with LLMs Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Generative Large Language Models (LLMs) like GPT, Gemini, and Llama are transforming Information Retrieval, enabling new and more effective approaches to document retrieval and … |
G. Zuccon; Shengyao Zhuang; Xueguang Ma; | Proceedings of the 48th International ACM SIGIR Conference … | 2025-07-13 |
| 986 | CADmium: Fine-Tuning Code Language Models for Text-Driven Sequential CAD Design Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Because simple metrics often failto reflect the quality of generated objects, we introduce geometric andtopological metrics based on sphericity, mean curvature, and Eulercharacteristic to provide richer structural insights. |
Prashant Govindarajan; Davide Baldelli; Jay Pathak; Quentin Fournier; Sarath Chandar; | arxiv-cs.GR | 2025-07-13 |
| 987 | The Effects of Demographic Instructions on LLM Personas Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Using demographic data from Twitter, we employ large language models (LLMs) to personalize the identification of sexism. |
ANGEL FELIPE MAGNOSS\~{A}O DE PAULA et. al. | sigir | 2025-07-13 |
| 988 | OPENXRD: A Comprehensive Benchmark and Enhancement Framework for LLM/MLLM XRD Question Answering Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This work presents OPENXRD, an open-book pipeline designed forcrystallography question answering, which integrates textual prompts withconcise supporting content generated by GPT-4.5. |
ALI VOSOUGHI et. al. | arxiv-cs.CL | 2025-07-12 |
| 989 | When Developer Aid Becomes Security Debt: A Systematic Analysis of Insecure Behaviors in LLM Coding Agents Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We developed a high-precision detection systemthat identified four major vulnerability categories, with information exposure(CWE-200) being the most prevalent one. |
Matous Kozak; Roshanak Zilouchian Moghaddam; Siva Sivaraman; | arxiv-cs.AI | 2025-07-12 |
| 990 | Universal Approximation Theorem for A Single-Layer Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Our main contribution is a universal approximation theoremfor Transformers: we prove that a single-layer Transformer, comprising oneself-attention layer followed by a position-wise feed-forward network with ReLUactivation, can approximate any continuous sequence-to-sequence mapping on acompact domain to arbitrary precision. |
Esmail Gumaan; | arxiv-cs.LG | 2025-07-11 |
| 991 | Intelligent Text Similarity Assessment Using Roberta with Integrated Chaotic Perturbation Optimization Techniques Related Papers Related Patents Related Grants Related Venues Related Experts View Save |
Esraa Hassan; Amira Samy Talaat; M. A. Elsabagh; | J. Big Data | 2025-07-11 |
| 992 | Detecting Fake News in Urdu Language Using Machine Learning, Deep Learning, and Large Language Model-Based Approaches Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Fake news is false or misleading information that looks like real news and spreads through traditional and social media. It has a big impact on our social lives, especially in … |
M. Farooq; Syed Muhammad Asadullah Gilani; Muhammad Faraz Manzoor; Momina Shaheen; | Inf. | 2025-07-10 |
| 993 | An Experimental Evaluation of Pre-Trained Models for Efficient and Accurate Record Linkage Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Record linkage in noisy and heterogeneous datasets remains a persistent challenge in data integration. In this work, we investigate the impact of various pre-trained … |
Dimitrios Karapiperis; G. Feretzakis; V. Verykios; | 2025 16th International Conference on Information, … | 2025-07-10 |
| 994 | Large Language Model for Extracting Complex Contract Information in Industrial Scenes Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper proposes a high-quality dataset construction method for complexcontract information extraction tasks in industrial scenarios and fine-tunes alarge language model based on this dataset. |
Yunyang Cao; Yanjun Li; Silong Dai; | arxiv-cs.CL | 2025-07-09 |
| 995 | Transfer Learning and Sentiment Analysis of Lebanese Dialect Data Using A Multilingual Deep Learning Approach Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: With the exponential growth in digitally created content and the surge in internet users, the challenges of handling and analyzing large volumes of data have increased, … |
R. Haraty; Mira Chehade; | Int. J. Speech Technol. | 2025-07-09 |
| 996 | Encoder-Only Transformer for Detecting Multiple Neurodegenerative Diseases from Gait Analysis Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Neurodegenerative diseases (NDDs) cause, among other symptoms, motor impairment. Given the incurable nature of the NDDs, several studies have investigated gait using artificial … |
Giordana de Farias F. B. Bucci; J. Felix; Rogerio Salvini; Hugo A. D. Nascimento; Fabrízzio Soares; | 2025 IEEE 49th Annual Computers, Software, and Applications … | 2025-07-08 |
| 997 | Comparative Analysis of BERT and GPT for Classifying Crisis News with Sudan Conflict As An Example Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: To obtain actionable information for humanitarian and other emergency responses, an accurate classification of news or events is critical. Daily news and social media are hard to … |
YAHYA MASRI et. al. | Algorithms | 2025-07-08 |
| 998 | ETT: Expanding The Long Context Understanding Capability of LLMs at Test-Time Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, weintroduce \ourmodelacronym~(Extend at Test-Time), method for extending thecontext length of short context Transformer-based LLMs, with constant memoryrequirement and linear computation overhead. |
Kiarash Zahirnia; Zahra Golpayegani; Walid Ahmed; Yang Liu; | arxiv-cs.CL | 2025-07-08 |
| 999 | AI-Generated Text Detection Using RoBERTa: A Generalizability and Explainability Analysis Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: With the rise of AI-generated text, the need for efficient detectors that perform well on various kinds of text generated by different models and prompts is increasing. We trained … |
Karla Schäfer; Martin Steinebach; | 2025 IEEE 49th Annual Computers, Software, and Applications … | 2025-07-08 |
| 1000 | Advancing Mental Disorder Detection: A Comparative Evaluation of Transformer and LSTM Architectures on Social Media Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The rising prevalence of mental health disorders necessitates the development of robust, automated tools for early detection and monitoring. Recent advances in Natural Language … |
Khalid Hasan; Jamil Saquer; Mukulika Ghosh; | 2025 IEEE 49th Annual Computers, Software, and Applications … | 2025-07-08 |