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 | 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 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 |
| 2 | 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 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 |
| 3 | Post-Training LLMs As Better Decision-Making Agents: A Regret-Minimization Approach Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 4 | Evaluating AI Models for Autograding Explain in Plain English Questions: Challenges and Considerations Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 5 | 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 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 |
| 6 | 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 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 |
| 7 | How Different Tokenization Algorithms Impact LLMs and Transformer Models for Binary Code Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 8 | From GPT to LLaMA: Tracing The Growth of Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 9 | 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 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 |
| 10 | Chronic Kidney Disease Prognosis Prediction Using Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 11 | 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 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 |
| 12 | Prompting for Policy: Forecasting Macroeconomic Scenarios with Synthetic LLM Personas Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 13 | No-Human in The Loop: Agentic Evaluation at Scale for Recommendation Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 14 | Targeted Error Correction in Knowledge Distillation: Small Language Models Surpass GPT Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 15 | Transcription Accuracy of Automatic Speech Recognition for Orthodontic Clinical Records Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 16 | 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 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 |
| 17 | LLMs As Judges: Toward The Automatic Review of GSN-compliant Assurance Cases Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 18 | Prompt Injection As An Emerging Threat: Evaluating The Resilience of Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 19 | 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 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 |
| 20 | 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 |
Mustafa Demirbilek; Sevim Özulukale Demirbilek; | Acta Infologica | 2025-11-03 |
| 21 | Foundations of Domain-specific Large Language Models for Islamic Studies: A Comprehensive Review Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 22 | Evaluating GPT-4’s Ability to Generate Informed Consent Material for Genetic Testing Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 23 | 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 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 |
| 24 | 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 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 |
| 25 | Performance of Large Language Models in Analyzing Common Hypertension Scenarios Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study evaluated the accuracy and safety of hypertension management recommendations generated by 3 LLMs. |
JALEH ZAND et. al. | Hypertension | 2025-11-03 |
| 26 | Extracting Linguistic Information from Large Language Models: Syntactic Relations and Derivational Knowledge Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a study of the linguistic knowledge and generalization capabilities of Large Language Models (LLMs), focusing ontheir morphosyntactic competence. |
Tsedeniya Kinfe Temesgen; Marion Di Marco; Alexander Fraser; | emnlp | 2025-11-02 |
| 27 | Speculating LLMs’ Chinese Training Data Pollution from Their Tokens Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 28 | 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 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 |
| 29 | How Accurate Are LLMs at Multi-Question Answering on Conversational Transcripts? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we explore the capabilities of LLMs to answer multiple questions based on the same conversational context. |
Xiliang Zhu; Shi Zong; David Rossouw; | emnlp | 2025-11-02 |
| 30 | 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 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 |
| 31 | Discursive Circuits: How Do Language Models Understand Discourse Relations? Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 32 | Table-LLM-Specialist: Language Model Specialists for Tables Using Iterative Fine-tuning Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 33 | Training Compute-optimal Transformer Encoder Models Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 34 | Large Language Models and Futures Price Factors in China Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 35 | 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 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 |
| 36 | Improving Cross Lingual Transfer By Pretraining with Active Forgetting Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 37 | Personality Matters: User Traits Predict LLM Preferences in Multi-Turn Collaborative Tasks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: As Large Language Models (LLMs) increasingly integrate into everyday workflows, where users shape outcomes through multi-turn collaboration, a critical question emerges: do users with different personality traits systematically prefer certain LLMs over others? |
Sarfaroz Yunusov; Kaige Chen; Kazi Nishat Anwar; Ali Emami; | emnlp | 2025-11-02 |
| 38 | Trojsten Benchmark: Evaluating LLM Problem-Solving in Slovak STEM Competition Problems Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 39 | Evaluating AI for Finance: Is AI Credible at Assessing Investment Risk Appetite? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We assess whether AI systems can credibly evaluate investment risk appetite—a task that must be thoroughly validated before automation. |
DIVIJ CHAWLA et. al. | emnlp | 2025-11-02 |
| 40 | 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 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 |
| 41 | A Generative Pre-Trained Language Model for Channel Prediction in Wireless Communications Systems Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 42 | Can Large Language Models Unlock Novel Scientific Research Ideas? Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View 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 |
| 43 | DINT Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 44 | SCRIBE: Structured Chain Reasoning for Interactive Behaviour Explanations Using Tool Calling Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 45 | 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 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 |
| 46 | Integral Transformer: Denoising Attention, Not Too Much Not Too Little Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 47 | Mixture of Languages: Improved Multilingual Encoders Through Language Grouping Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose Mixture of Languages (MoL), a new strategy to pretrain largely multilingual encoders. |
JOÃO MARIA JANEIRO et. al. | emnlp | 2025-11-02 |
| 48 | Detecting Legal Citations in United Kingdom Court Judgments Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 49 | 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 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 |
| 50 | REARANK: Reasoning Re-ranking Agent Via Reinforcement Learning Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present REARANK, a large language model (LLM)-based listwise reasoning rerank- ing agent. |
Le Zhang; Bo Wang; Xipeng Qiu; Siva Reddy; Aishwarya Agrawal; | emnlp | 2025-11-02 |
| 51 | IIET: Efficient Numerical Transformer Via Implicit Iterative Euler Method Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 52 | Exploring and Mitigating Gender Bias in Encoder-Based Transformer Models Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 53 | 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 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 |
| 54 | Photonic Transformer Chip: Interference Is All You Need Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Here we propose an attention mechanism relying solely on the runtime-programable optical-interference. |
YE TIAN et. al. | PhotoniX | 2025-10-31 |
| 55 | 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 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 |
| 56 | 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 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 |
| 57 | Enhancing Sentiment Classification with Machine Learning and Combinatorial Fusion Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 58 | Simulating and Experimenting with Social Media Mobilization Using LLM Agents Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 59 | Who Has The Final Say? Conformity Dynamics in ChatGPT’s Selections Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 60 | EdgeRunner 20B: Military Task Parity with GPT-5 While Running on The Edge Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 61 | Analysing The Role of LLMs in Cybersecurity Incident Management Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 62 | Financial Sentiment Analysis with FUNNEL: Filtered UNion for NER-based Ensemble Labeling Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 63 | 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 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 |
| 64 | 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 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 |
| 65 | 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 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 |
| 66 | Advancing Urdu Named Entity Recognition: Deep Learning for Aspect Targeting Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 67 | Context‐Aware Prompt Engineering for Large Language Models in Autonomous Vehicles Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 68 | 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 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 |
| 69 | DynBERG: Dynamic BERT-based Graph Neural Network for Financial Fraud Detection Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 70 | 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 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 |
| 71 | Aspect-Based Sentiment Analysis for Turkish Reviews Using Token and Sequential Classification Methods Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 72 | ComboBench: Can LLMs Manipulate Physical Devices to Play Virtual Reality Games? Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 73 | An Event Study on The Market Impacts of The Release of Major AI Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The event study approach and the market model are applied to investigate the abnormal stock returns of Microsoft and Google after the release of models (namely, ChatGPT, GPT-4 and Gemini 2.0) related to either of the companies. |
Haichuan Xi; Congqi Yan; Haoxuan Liu; Houfu Xu; | Advances in Economics, Management and Political Sciences | 2025-10-28 |
| 74 | 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 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 |
| 75 | Evaluating LLMs on Generating Age-Appropriate Child-Like Conversations Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 76 | RefleXGen:The Unexamined Code Is Not Worth Using Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces RefleXGen, an innovative methodthat significantly enhances code security by integrating Retrieval-AugmentedGeneration (RAG) techniques with guided self-reflection mechanisms inherent inLLMs. |
BIN WANG et. al. | arxiv-cs.SE | 2025-10-27 |
| 77 | LLMs As Mediators: Can They Diagnose Conflicts Accurately? Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 78 | Validating Formal Specifications with LLM-generated Test Cases Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Inparticular, we focus on test cases for structural requirements of simple domainmodels formalized in the Alloy specification language. |
Alcino Cunha; Nuno Macedo; | arxiv-cs.SE | 2025-10-27 |
| 79 | AI-Driven Carbon Monitoring: Transformer-Based Reconstruction of Atmospheric CO2 in Canadian Poultry Regions Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present aSpatiotemporal Vision Transformer with Wavelets (ST-ViWT) framework thatreconstructs continuous, uncertainty-quantified XCO2 fields from OCO-2 acrosssouthern Canada, emphasizing poultry-intensive regions. |
Padmanabhan Jagannathan Prajesh; Kaliaperumal Ragunath; Miriam Gordon; Bruce Rathgeber; Suresh Neethirajan; | arxiv-cs.LG | 2025-10-26 |
| 80 | 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 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 |
| 81 | Evaluating Large Language Models for Turboshaft Engine Torque Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 82 | Integration of LLMs for Multitasking Workload Prediction in Mixed Reality Environments Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 83 | Supervised Fine-Tuning or In-Context Learning? Evaluating LLMs for Clinical NER Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 84 | 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 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 |
| 85 | 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 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 |
| 86 | You Don’t Need Prompt Engineering Anymore: The Prompting Inversion Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 87 | InterpDetect: Interpretable Signals for Detecting Hallucinations in Retrieval-Augmented Generation Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 88 | Jailbreak Mimicry: Automated Discovery of Narrative-Based Jailbreaks for Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 89 | 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 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 |
| 90 | HalleluBERT: Let Every Token That Has Meaning Bear Its Weight Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 91 | SindBERT, The Sailor: Charting The Seas of Turkish NLP Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 92 | 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 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 |
| 93 | A Coherence-Based Measure of AGI Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 94 | 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 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 |
| 95 | 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 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 |
| 96 | A Review of The Application of Transformer in Financial Market Risk Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 97 | 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 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 |
| 98 | Evaluating LLM Story Generation Through Large-scale Network Analysis of Social Structures Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Weintroduce a novel, scalable methodology for evaluating LLM story generation byanalyzing underlying social structures in narratives as signed characternetworks. To demonstrate its effectiveness, we conduct a large-scalecomparative analysis using networks from over 1,200 stories, generated by fourleading LLMs (GPT-4o, GPT-4o mini, Gemini 1.5 Pro, and Gemini 1.5 Flash) and ahuman-written corpus. |
Hiroshi Nonaka; K. E. Perry; | arxiv-cs.CL | 2025-10-21 |
| 99 | Cultural Alien Sampler: Open-ended Art Generation Balancing Originality and Coherence Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 100 | EfficientNav: Towards On-Device Object-Goal Navigation with Navigation Map Caching and Retrieval Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose EfficientNav to enable on-deviceefficient LLM-based zero-shot ObjNav. |
ZEBIN YANG et. al. | arxiv-cs.RO | 2025-10-21 |
| 101 | Misinformation Detection Using Large Language Models with Explainability Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 102 | Exploration of Stability Judgments: Assessing Multimodal LLMs in Game-Inspired Physical Reasoning Tasks Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 103 | Explainable Bilingual Medical-Question-Answering Model Using Ensemble Learning Technique Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 104 | SODBench: A Large Language Model Approach to Documenting Spreadsheet Operations Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces SpreadsheetOperations Documentation (SOD), an AI task that involves generatinghuman-readable explanations from spreadsheet operations. |
Amila Indika; Igor Molybog; | arxiv-cs.SE | 2025-10-21 |
| 105 | A Graph Signal Processing Framework for Hallucination Detection in Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 106 | Chain-of-Thought Reasoning Improves Context-Aware Translation with Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 107 | TAR3D: Creating High-Quality 3D Assets Via Next-Part Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 108 | 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 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 |
| 109 | An Enhanced Dual Transformer Contrastive Network for Multimodal Sentiment Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 110 | Predicting Software Developer Sentiment on Self-admitted Technical Debt Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 111 | Temporal-aware Query Routing for Real-time Video Instance Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Further analysis of the similarities between the outputs from adjacent frames at each transformer decoder layer reveals significant redundant computations within the transformer decoder. To address this issue, we introduce Temporal-Aware query Routing (TAR) mechanism. |
ZESEN CHENG et. al. | iccv | 2025-10-20 |
| 112 | HIS-GPT: Towards 3D Human-In-Scene Multimodal Understanding Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 113 | CARP: Visuomotor Policy Learning Via Coarse-to-Fine Autoregressive Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 114 | Rethinking Search: A Study of University Students’ Perspectives on Using LLMs and Traditional Search Engines in Academic Problem Solving Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Employinga mixed-methods approach, we surveyed 109 students from diverse disciplines andconducted in-depth interviews with 12 participants. |
Md. Faiyaz Abdullah Sayeedi; Md. Sadman Haque; Zobaer Ibn Razzaque; Robiul Awoul Robin; Sabila Nawshin; | arxiv-cs.HC | 2025-10-20 |
| 115 | MEG-GPT: A Transformer-based Foundation Model for Magnetoencephalography Data Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 116 | A Definition of AGI Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The lack of a concrete definition for Artificial General Intelligence (AGI)obscures the gap between today’s specialized AI and human-level cognition. Thispaper introduces a quantifiable framework to address this, defining AGI asmatching the cognitive versatility and proficiency of a well-educated adult. |
DAN HENDRYCKS et. al. | arxiv-cs.AI | 2025-10-20 |
| 117 | Visual Interestingness Decoded: How GPT-4o Mirrors Human Interests Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 118 | Can Transformer Memory Be Corrupted? Investigating Cache-Side Vulnerabilities in Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 119 | AI-Generated Text Detection in Low-Resource Languages: A Case Study on Urdu Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 120 | 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 |
RUSHMIN KHAZANCHI et. al. | Journal of Clinical Neuroscience | 2025-10-18 |
| 121 | Mixture of Experts Approaches in Dense Retrieval Tasks Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 122 | 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 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 |
| 123 | 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 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 |
| 124 | Reasoning-based LLMs Surpass Average Human Performance on Medical Social Skills Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 125 | First Attentions Last: Better Exploiting First Attentions for Efficient Transformer Training Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 126 | A Free Lunch in LLM Compression: Revisiting Retraining After Pruning Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 127 | A Novel GPT-Based Framework for Anomaly Detection in System Logs Summary Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 128 | 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 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 |
| 129 | AI-Powered Early Diagnosis of Mental Health Disorders from Real-World Clinical Conversations Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 130 | PUMA: Secure Inference of LLaMA-7B in Five Minutes Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View 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 |
| 131 | Leveraging Large Language Models to Generate Multiple-Choice Questions for Ophthalmology Education Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 132 | Assessing Web Search Credibility and Response Groundedness in Chat Assistants Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 133 | 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 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 |
| 134 | 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 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 |
| 135 | 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 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 |
| 136 | Modelado Semántico De Emergencias Del ECU 911 Con NLP Y Ontologías Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 137 | CRaFT: An Explanation-Based Framework for Evaluating Cultural Reasoning in Multilingual Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We apply the framework to 50culturally grounded questions from the World Values Survey, translated intoArabic, Bengali, and Spanish, and evaluate three models (GPT, DeepSeek, andFANAR) across over 2,100 answer-explanation pairs. |
Shehenaz Hossain; Haithem Afli; | arxiv-cs.CL | 2025-10-15 |
| 138 | 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 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 |
| 139 | NEUROXL-CRFNET: A HYBRID TRANSFORMER–GRAPH FRAMEWORK FOR AUTOMATED HEPATOCELLULAR CARCINOMA HISTOPATHOLOGY CLASSIFICATION Related Papers Related Patents Related Grants Related Venues Related Experts View 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 | |
| 140 | DETECTION OF MACHINE-GENERATED TEXT BY INTEGRATING ROBERTA EMBEDDINGS WITH TOPOLOGICAL FEATURES Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 141 | How Deep Is Representational Bias in LLMs? The Cases of Caste and Religion Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 142 | Timelygpt: Extrapolatable Transformer Pre-training for Long-term Time-series Forecasting in Healthcare Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 143 | Attribution Quality in AI-Generated Content:Benchmarking Style Embeddings and LLM Judges Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 144 | Toward LLM-Supported Automated Assessment of Critical Thinking Subskills Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 145 | 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 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 |
| 146 | Efficient Adaptive Transformer: An Empirical Study and Reproducible Framework Summary Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 147 | Refining Hybrid Genetic Search for CVRP Via Reinforcement Learning-Finetuned LLM Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 148 | 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 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 |
| 149 | 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 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 |
| 150 | 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 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 |
| 151 | BERT-Based Sentiment Analysis of Turkish E-Commerce Reviews: Star Ratings Versus Text Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 152 | 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 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 |
| 153 | DocReward: A Document Reward Model for Structuring and Stylizing Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 154 | 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 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 |
| 155 | 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 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 |
| 156 | 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 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 |
| 157 | HiligayNER: A Baseline Named Entity Recognition Model for Hiligaynon Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 158 | Multi-Transformer-Based Ensemble Embedding Model for Enhanced Vector Search in NoSQL Database: A Comparative Statistical and Performance Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study uses all-MiniLM-L6-v2, paraphrase-MiniLM-L6-v2 and all-distilroberta-v1 transformer-based embedding models to find the similarity search for Wikipedia documents. |
NARUT BUTPLOY et. al. | International Journal of Mathematical, Engineering and … | 2025-10-12 |
| 159 | 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 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 |
| 160 | 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 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 |
| 161 | Deliberative Dynamics and Value Alignment in LLM Debates Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 162 | 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 |
HUANG HUANG et. al. | Complex & Intelligent Systems | 2025-10-10 |
| 163 | Learning Bug Context for PyTorch-to-JAX Translation with LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 164 | 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 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 |
| 165 | Weight Initialization and Variance Dynamics in Deep Neural Networks and Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 166 | Domain-Adapted Pre-trained Language Models for Implicit Information Extraction in Crash Narratives Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 167 | Hallucination Filtering in Radiology Vision-Language Models Using Discrete Semantic Entropy Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 168 | 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 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 |
| 169 | ACE: Attribution-Controlled Knowledge Editing for Multi-hop Factual Recall Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 170 | Large Language Models: A Paradigm Shift for Dementia Diagnosis and Care Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 171 | Measuring Moral LLM Responses in Multilingual Capacities Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Our study shows that GPT-5 performedthe best on average in each category, while other models displayed moreinconsistency across language and category. |
Kimaya Basu; Savi Kolari; Allison Yu; | arxiv-cs.CL | 2025-10-09 |
| 172 | Sentiment-Enhanced Cyberbullying Detection Models on Social Media Platforms Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 173 | 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 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 |
| 174 | Single Layer Tiny Co$^4$ Outpaces GPT-2 and GPT-BERT Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 175 | 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 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 |
| 176 | Unveiling The Physical Meaning of Transformer Attention in Neural Network Quantum States: A Conditional Mutual Information Perspective Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose that the attention mechanism-a central module in Transformer architectures-explicitly models the conditional information flow between orbitals. |
TIANYU RUAN et. al. | Chinese Physics B | 2025-10-09 |
| 177 | FAR-AM: A Hybrid Attention Framework for Fire Cause Classification Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 178 | 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 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 |
| 179 | RETRIEVAL AUGMENTED NEURAL ADAPTERS FOR DOMAIN SPECIFIC CUSTOMIZATION OF LARGE LANGUAGE MODELS Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 180 | GPT-5 Model Corrected GPT-4V’s Chart Reading Errors, Not Prompting Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 181 | On The Effectiveness of Limited-data Large Language Model Fine-tuning for Arabic Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 182 | 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 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 |
| 183 | Judgments of Learning Distinguish Humans from Large Language Models in Predicting Memory Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 184 | Evaluating The Impact of Stimulus Quality in Investigations of LLM Language Performance Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 185 | Vision Transformer for Transient Noise Classification Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 186 | Audit-style Framework for Evaluating Bias in Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose an evaluation framework for assessing whether a system exhibits biased behavior. |
Peter Baldwin; | Frontiers in Education | 2025-10-06 |
| 187 | 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 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 |
| 188 | MacroBench: A Novel Testbed for Web Automation Scripts Via Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce MacroBench, a code-first benchmark that evaluates whether LLMscan synthesize reusable browser-automation programs (macros) fromnatural-language goals by reading HTML/DOM and emitting Selenium. |
Hyunjun Kim; Sejong Kim; | arxiv-cs.SE | 2025-10-05 |
| 189 | AgentTypo: Adaptive Typographic Prompt Injection Attacks Against Black-box Multimodal Agents Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 190 | 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 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 |
| 191 | Perbandingan Bidirectional Encoder Representations from Transformers (BERT) Language Model Pada Deteksi Emosi Summary Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 192 | Annotate Rhetorical Relations with INCEpTION: A Comparison with Automatic Approaches Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 193 | LLM, Reporting In! Medical Information Extraction Across Prompting, Fine-tuning and Post-correction Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 194 | 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 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 |
| 195 | Hierarchical Semantic Retrieval with Cobweb Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 196 | Enhanced Arabic-language Cyberbullying Detection: Deep Embedding and Transformer (BERT) Approaches Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 197 | 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 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 |
| 198 | ENLighten: Lighten The Transformer, Enable Efficient Optical Acceleration Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To address thesechallenges, we introduce a hardware–software co-design framework. |
HANQING ZHU et. al. | arxiv-cs.ET | 2025-10-02 |
| 199 | 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 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 |
| 200 | Hybrid Dialogue State Tracking for Persian Chatbots: A Language Model-Based Approach Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 201 | 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 |
ZHUANGJI WANG et. al. | Comput. Electron. Agric. | 2025-10-01 |
| 202 | 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 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 |
| 203 | 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 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 |
| 204 | Detecting Hope Across Languages: Multiclass Classification for Positive Online Discourse Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 205 | 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 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 |
| 206 | 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 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 |
| 207 | Using GPT to Build A Project Management Assistant for Jira Environments Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 208 | Large Language Models Inference Engines Based on Spiking Neural Networks Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 209 | LLM Based Sentiment Classification From Bangladesh E-Commerce Reviews Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 210 | 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 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 |
| 211 | Federated Learning Meets LLMs: Feature Extraction From Heterogeneous Clients Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 212 | An Agent-Based Framework for Automated Higher-Voice Harmony Generation Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 213 | Ensembling Multilingual Transformers for Robust Sentiment Analysis of Tweets Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 214 | 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 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 |
| 215 | Quant Fever, Reasoning Blackholes, Schrodinger’s Compliance, and More: Probing GPT-OSS-20B Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 216 | FraudTransformer: Time-Aware GPT for Transaction Fraud Detection Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 217 | BeyondBench: Benchmark-Free Evaluation of Reasoning in Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 218 | WirelessMathLM: Teaching Mathematical Reasoning for LLMs in Wireless Communications with Reinforcement Learning Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 219 | An Senegalese Legal Texts Structuration Using LLM-augmented Knowledge Graph Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study examines the application of artificial intelligence (AI) and largelanguage models (LLM) to improve access to legal texts in Senegal’s judicialsystem. |
Oumar Kane; Mouhamad M. Allaya; Dame Samb; Mamadou Bousso; | arxiv-cs.CL | 2025-09-27 |
| 220 | The Impact of Role Design in In-Context Learning for Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 221 | Deep Learning for Oral Health: Benchmarking ViT, DeiT, BEiT, ConvNeXt, and Swin Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 222 | Multi-Agent Path Finding Via Offline RL and LLM Collaboration Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 223 | Teaching Transformers to Solve Combinatorial Problems Through Efficient Trial & Error Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Despite their proficiency in various language tasks, Large Language Models(LLMs) struggle with combinatorial problems like Satisfiability, TravelingSalesman Problem, or even basic arithmetic. We address this gap through a novelapproach for solving problems in the class NP. |
Panagiotis Giannoulis; Yorgos Pantis; Christos Tzamos; | arxiv-cs.LG | 2025-09-26 |
| 224 | Large Language Models Management of Medications: Three Performance Analyses Summary Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 225 | GPT-4 for Occlusion Order Recovery Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 226 | An Improved Quantum Software Challenges Classification Approach Using Transfer Learning and Explainable AI Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We conducted studies to classifyquestions into various challenges. |
NEK DIL KHAN et. al. | arxiv-cs.SE | 2025-09-25 |
| 227 | Extracting Conceptual Knowledge to Locate Software Issues Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 228 | LLM-Based Support for Diabetes Diagnosis: Opportunities, Scenarios, and Challenges with GPT-5 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study evaluates GPT-5, the latest generative pre-trainedtransformer, using a simulation framework built entirely on synthetic casesaligned with ADA Standards of Care 2025 and inspired by public datasetsincluding NHANES, Pima Indians, EyePACS, and MIMIC-IV. |
Gaurav Kumar Gupta; Nirajan Acharya; Pranal Pande; | arxiv-cs.CL | 2025-09-25 |
| 229 | 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 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 |
| 230 | Dual-Path Phishing Detection: Integrating Transformer-Based NLP with Structural URL Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 231 | SINAI at ERisk@CLEF 2025: Transformer-Based and Conversational Strategies for Depression Detection Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 232 | IA Aplicada Al Análisis Del Conflicto Irán-Israel: Mapeo De Discursos En YouTube Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 233 | 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 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 |
| 234 | Hierarchical Resolution Transformers: A Wavelet-Inspired Architecture for Multi-Scale Language Understanding Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 235 | 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 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 |
| 236 | 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 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 |
| 237 | Longitudinal Monitoring of LLM Content Moderation of Social Issues Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce AI Watchman, a longitudinal auditing system to publiclymeasure and track LLM refusals over time, to provide transparency into animportant and black-box aspect of LLMs. |
Yunlang Dai; Emma Lurie; Danaé Metaxa; Sorelle A. Friedler; | arxiv-cs.CL | 2025-09-24 |
| 238 | Systematic Comparative Analysis of Large Pretrained Language Models on Contextualized Medication Event Extraction Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 239 | Thinking While Listening: Simple Test Time Scaling For Audio Classification Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 240 | Confidence Calibration in Large Language Model-Based Entity Matching Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 241 | Human-Annotated NER Dataset for The Kyrgyz Language Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 242 | Gödel Test: Can Large Language Models Solve Easy Conjectures? Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 243 | Beyond Diagnosis: Evaluating Multimodal LLMs for Pathology Localization in Chest Radiographs Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 244 | 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 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 |
| 245 | Scattering Transformer: A Training-Free Transformer Architecture for Heart Murmur Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We evaluate our approach on the public CirCorDigiScope dataset, directly comparing it against leading general-purposefoundational models. |
Rami Zewail; | arxiv-cs.SD | 2025-09-22 |
| 246 | Evaluating Generative AI As An Educational Tool for Radiology Resident Report Drafting Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 247 | Scale-free Characteristics of Multilingual Legal Texts and The Limitations of LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present a comparative analysis of text complexity across domains usingscale-free metrics. |
Haoyang Chen; Kumiko Tanaka-Ishii; | arxiv-cs.CL | 2025-09-22 |
| 248 | 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 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 |
| 249 | Mental Multi-class Classification on Social Media: Benchmarking Transformer Architectures Against LSTM Models Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 250 | 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 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 |
| 251 | 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 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 |
| 252 | 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 |
C. Roșca; Adrian Stancu; | Comput. Stand. Interfaces | |
| 253 | Interplay Between Belief Propagation and Transformer: Differential-Attention Message Passing Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 254 | 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 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 |
| 255 | 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 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 |
| 256 | Language Modeling with Learned Meta-Tokens Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 257 | From Pixels to Urban Policy-Intelligence: Recovering Legacy Effects of Redlining with A Multimodal LLM Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper shows how a multimodal large language model (MLLM) can expandurban measurement capacity and support tracking of place-based policyinterventions. |
Anthony Howell; Nancy Wu; Sharmistha Bagchi; Yushim Kim; Chayn Sun; | arxiv-cs.CY | 2025-09-18 |
| 258 | Diffusion-Based Cross-Modal Feature Extraction for Multi-Label Classification Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 259 | HausaMovieReview: A Benchmark Dataset for Sentiment Analysis in Low-Resource African Language Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 260 | Simulating Clinical AI Assistance Using Multimodal LLMs: A Case Study in Diabetic Retinopathy Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 261 | 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 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 |
| 262 | 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 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 |
| 263 | 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 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 |
| 264 | 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 Highlight: We propose and evaluate a noveldefense technique called Adversarial Fine-Tuning. |
Gustavo Sandoval; Denys Fenchenko; Junyao Chen; | arxiv-cs.CR | 2025-09-15 |
| 265 | 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 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 |
| 266 | 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 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 |
| 267 | 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 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 |
| 268 | 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 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 |
| 269 | Evaluating Large Language Models for Evidence-Based Clinical Question Answering Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 270 | Understanding AI Evaluation Patterns: How Different GPT Models Assess Vision-Language Descriptions Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 271 | Long Context Automated Essay Scoring with Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 272 | Beyond Token Limits: Assessing Language Model Performance on Long Text Classification Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 273 | PolyTruth: Multilingual Disinformation Detection Using Transformer-Based Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 274 | Automated MCQA Benchmarking at Scale: Evaluating Reasoning Traces As Retrieval Sources for Domain Adaptation of Small Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a scalable, modular framework forgenerating multiple-choice question-answering (MCQA) benchmarks directly fromlarge corpora of scientific papers. |
OZAN GOKDEMIR et. al. | arxiv-cs.CL | 2025-09-12 |
| 275 | 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 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 |
| 276 | WALL: A Web Application for Automated Quality Assurance Using Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Future work aims to enhance WALL’scapabilities by integrating open-source LLMs and eliminating humanintervention, paving the way for fully automated code quality management. |
Seyed Moein Abtahi; Akramul Azim; | arxiv-cs.SE | 2025-09-11 |
| 277 | Agentic LLMs for Question Answering Over Tabular Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a Natural Language to SQL (NL-to-SQL) approachleveraging large language models (LLMs) such as GPT-4o, GPT-4o-mini, andDeepSeek v2:16b to generate SQL queries dynamically. |
Rishit Tyagi; Mohit Gupta; Rahul Bouri; | arxiv-cs.CL | 2025-09-11 |
| 278 | 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 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 |
| 279 | Instructional Prompt Optimization for Few-Shot LLM-Based Recommendations on Cold-Start Users Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 280 | 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 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 |
| 281 | Towards Knowledge-Aware Document Systems: Modeling Semantic Coverage Relations Via Answerability Detection Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 282 | 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 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 |
| 283 | 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 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 |
| 284 | 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 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 |
| 285 | From Noise to Narrative: Tracing The Origins of Hallucinations in Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In the present work, we establish how and whenhallucinations arise in pre-trained transformer models through conceptrepresentations captured by sparse autoencoders, under scenarios withexperimentally controlled uncertainty in the input space. |
Praneet Suresh; Jack Stanley; Sonia Joseph; Luca Scimeca; Danilo Bzdok; | arxiv-cs.LG | 2025-09-08 |
| 286 | KatotohananQA: Evaluating Truthfulness of Large Language Models in Filipino Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Large Language Models (LLMs) achieve remarkable performance across varioustasks, but their tendency to produce hallucinations limits reliable adoption.Benchmarks such as TruthfulQA have been developed to measure truthfulness, yetthey are primarily available in English, leaving a gap in evaluating LLMs inlow-resource languages. To address this, we present KatotohananQA, a Filipinotranslation of the TruthfulQA benchmark. |
Lorenzo Alfred Nery; Ronald Dawson Catignas; Thomas James Tiam-Lee; | arxiv-cs.CL | 2025-09-07 |
| 287 | A Survey of The State-of-the-Art in Conversational Question Answering Systems Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 288 | 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 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 |
| 289 | 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 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 |
| 290 | Expanding Foundational Language Capabilities in Open-Source LLMs Through A Korean Case Study Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 291 | Comparative Analysis of Transformer Models in Disaster Tweet Classification for Public Safety Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 292 | A RoBERTa-Based Functional Syntax Annotation Model for Chinese Texts Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 293 | Improving Narrative Classification and Explanation Via Fine Tuned Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 294 | Decoders Laugh As Loud As Encoders Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 295 | 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 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 |
| 296 | Advancing Minority Stress Detection with Transformers: Insights from The Social Media Datasets Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Theoretical analysis reveals that modeling socialconnectivity and conversational context via graph augmentation sharpens themodels’ ability to identify key linguistic markers such as identityconcealment, internalized stigma, and calls for support, suggesting thatgraph-enhanced transformers offer the most reliable foundation for digitalhealth interventions and public health policy. |
Santosh Chapagain; Cory J Cascalheira; Shah Muhammad Hamdi; Soukaina Filali Boubrahimi; Jillian R. Scheer; | arxiv-cs.CL | 2025-09-02 |
| 297 | 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 Highlight: This study presents a hybrid framework for predicting movie success. |
Wenlan Xie; | arxiv-cs.SI | 2025-09-02 |
| 298 | 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 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 |
| 299 | 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 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 |
| 300 | TransGAT: Transformer-Based Graph Neural Networks for Multi-Dimensional Automated Essay Scoring Summary Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 301 | A Multi-target Bayesian Transformer Framework for Predicting Cardiovascular Disease Biomarkers During Pandemics Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 302 | Generative Goal Modeling Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 303 | LLM Encoder Vs. Decoder: Robust Detection of Chinese AI-Generated Text with LoRA Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 304 | 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 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 |
| 305 | 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 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 |
| 306 | A Multi-Strategy Approach for AI-Generated Text Detection Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 307 | No Clustering, No Routing: How Transformers Actually Process Rare Tokens Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 308 | Quantum-Optimized Selective State Space Model for Efficient Time Series Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 309 | 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 Highlight: Introduction: Large language models (LLM) have shown great potential inclinical decision support. |
UGUR DINC et. al. | arxiv-cs.CV | 2025-08-29 |
| 310 | 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 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 |
| 311 | GIER: Gap-Driven Self-Refinement for Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce GIER (Gap-driven Iterative Enhancement of Responses), a generalframework for improving large language model (LLM) outputs throughself-reflection and revision based on conceptual quality criteria. |
Rinku Dewri; | arxiv-cs.CL | 2025-08-29 |
| 312 | Challenges and Applications of Large Language Models: A Comparison of GPT and DeepSeek Family of Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This article aims to guide AI researchers, developers, anddecision-makers in understanding current LLM capabilities, limitations, andbest practices. |
Shubham Sharma; Sneha Tuli; Narendra Badam; | arxiv-cs.CL | 2025-08-29 |
| 313 | 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 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 |
| 314 | Speech Emotion Recognition Via Entropy-Aware Score Selection Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 315 | Multi-Lingual Implicit Discourse Relation Recognition with Multi-Label Hierarchical Learning Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 316 | Benchmarking GPT-5 for Biomedical Natural Language Processing Summary Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 317 | Benchmarking GPT-5 for Biomedical Natural Language Processing Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 318 | GUARD: Guideline Upholding Test Through Adaptive Role-play and Jailbreak Diagnostics for LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 319 | Cross-Platform E-Commerce Product Categorization and Recategorization: A Multimodal Hierarchical Classification Approach Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 320 | Dhati+: Fine-tuned Large Language Models for Arabic Subjectivity Evaluation Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 321 | 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 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 |
| 322 | CAPE: Context-Aware Personality Evaluation Framework for Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 323 | CoFormer: Collaborating with Heterogeneous Edge Devices for Scalable Transformer Inference Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 324 | Scalable Object Detection in The Car Interior With Vision Foundation Models Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 325 | Breaking The Layer Barrier: Remodeling Private Transformer Inference with Hybrid CKKS and MPC Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 326 | A Retail-Corpus for Aspect-Based Sentiment Analysis with Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 327 | 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 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 |
| 328 | MahaParaphrase: A Marathi Paraphrase Detection Corpus and BERT-based Models Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 329 | Exploring Efficient Learning of Small BERT Networks with LoRA and DoRA Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 330 | School of Reward Hacks: Hacking Harmless Tasks Generalizes to Misaligned Behavior in LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 331 | Large Language Models As Universal Predictors? An Empirical Study on Small Tabular Datasets Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 332 | In-Context Algorithm Emulation in Fixed-Weight Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 333 | 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 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 |
| 334 | From Indirect Object Identification to Syllogisms: Exploring Binary Mechanisms in Transformer Circuits Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 335 | LLM-Assisted Semantic Alignment and Integration in Collaborative Model-Based Systems Engineering Using SysML V2 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes astructured, prompt-driven approach for LLM-assisted semantic alignment of SysMLv2 models. |
Zirui Li; Stephan Husung; Haoze Wang; | arxiv-cs.SE | 2025-08-22 |
| 336 | 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 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 |
| 337 | Strategic Sample Selection for Improved Clean-Label Backdoor Attacks in Text Classification Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 338 | 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 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 |
| 339 | 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 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 |
| 340 | Enhancing Targeted Adversarial Attacks on Large Vision-Language Models Via Intermediate Projector Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 341 | KillChainGraph: ML Framework for Predicting and Mapping ATT&CK Techniques Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 342 | Beyond GPT-5: Making LLMs Cheaper and Better Via Performance-Efficiency Optimized Routing Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 343 | Wavy Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, deep transformer modelsoften suffer from an over-smoothing issue, in which token representationsconverge to similar values as they pass through successive transformer blocks.In this paper, we establish an equivalence between the hidden-state dynamicsinduced by stacked attention layers and graph neural diffusion on a completegraph. From this perspective, over-smoothing can be interpreted as aconsequence of the dissipative nature of the underlying diffusion dynamics.Motivated by this physical interpretation, we propose Wavy Transformer, whichconsists of a novel attention layer based on second-order wavy dynamics. |
Satoshi Noguchi; Yoshinobu Kawahara; | arxiv-cs.LG | 2025-08-18 |
| 344 | Holistic Evaluation of Multimodal LLMs on Spatial Intelligence Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 345 | Exploring The Feasibility of LLMs for Automated Music Emotion Annotation Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 346 | 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 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 |
| 347 | 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 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 |
| 348 | The Structural Sources of Verb Meaning Revisited: Large Language Models Display Syntactic Bootstrapping Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 349 | Capabilities of GPT-5 Across Critical Domains: Is It The Next Breakthrough? Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 350 | Is ChatGPT-5 Ready for Mammogram VQA? Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 351 | Contextual Attention-Based Multimodal Fusion of LLM and CNN for Sentiment Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 352 | Recent Advances in Transformer and Large Language Models for UAV Applications Summary Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 353 | Hallucination in LLM-Based Code Generation: An Automotive Case Study Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 354 | Automated Building Heritage Assessment Using Street-Level Imagery Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 355 | 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 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 |
| 356 | The Impact of Large Language Models (LLMs) on Code Review Process Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 357 | 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 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 |
| 358 | Performance of GPT-5 in Brain Tumor MRI Reasoning Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 359 | SEQ-GPT: LLM-assisted Spatial Query Via Example Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 360 | 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 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 |
| 361 | Evaluating LLMs on Chinese Idiom Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, weintroduce IdiomEval, a framework with a comprehensive error taxonomy forChinese idiom translation. |
Cai Yang; Yao Dou; David Heineman; Xiaofeng Wu; Wei Xu; | arxiv-cs.CL | 2025-08-14 |
| 362 | Performance of GPT-5 Frontier Models in Ophthalmology Question Answering Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 363 | Echo-4o: Harnessing The Power of GPT-4o Synthetic Images for Improved Image Generation Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 364 | Understanding Textual Emotion Through Emoji Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 365 | NEFMind: Parameter-Efficient Fine-Tuning of Open-Source LLMs for Telecom APIs Automation Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 366 | UWB at WASSA-2024 Shared Task 2: Cross-lingual Emotion Detection Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 367 | Training-Free Text-Guided Color Editing with Multi-Modal Diffusion Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 368 | 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 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 |
| 369 | What Am I Missing Here?: Evaluating Large Language Models for Masked Sentence Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 370 | Training-Free ANN-to-SNN Conversion for High-Performance Spiking Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 371 | Capabilities of GPT-5 on Multimodal Medical Reasoning IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 372 | GPT-2 As A Compression Preprocessor: Improving Gzip for Structured Text Domains Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 373 | Arce: Augmented Roberta with Contextualized Elucidations for Ner in Automated Rule Checking Summary Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 374 | Crisp Attention: Regularizing Transformers Via Structured Sparsity Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 375 | LLMCARE: Alzheimer’s Detection Via Transformer Models Enhanced By LLM-Generated Synthetic Data Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 376 | Gpt-oss-120b & Gpt-oss-20b Model Card IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 377 | AntiCheatPT: A Transformer-Based Approach to Cheat Detection in Competitive Computer Games Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 378 | 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 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 |
| 379 | 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 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 |
| 380 | Leveraging Large Language Models for SQL Behavior-based Database Intrusion Detection Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 381 | 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 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 |
| 382 | Advancing Hate Speech Detection with Transformers: Insights from The MetaHate Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 383 | Compressing Large Language Models with PCA Without Performance Loss Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 384 | A Reproducible, Scalable Pipeline for Synthesizing Autoregressive Model Literature Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 385 | 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 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 |
| 386 | Can Large Language Models Bridge The Gap in Environmental Knowledge? Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 387 | Estimating Worst-Case Frontier Risks of Open-Weight LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 388 | GP and LLMs for Program Synthesis: No Clear Winners Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 389 | R2GenKG: Hierarchical Multi-modal Knowledge Graph for LLM-based Radiology Report Generation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 390 | From Text to Trajectories: GPT-2 As An ODE Solver Via In-Context Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 391 | 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 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 |
| 392 | Contextual Graph Transformer: A Small Language Model for Enhanced Engineering Document Information Extraction Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 393 | Interference Matrix: Quantifying Cross-Lingual Interference in Transformer Encoders Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 394 | Prompt to Pwn: Automated Exploit Generation for Smart Contracts Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present \textsc{ReX}, a frameworkintegrating LLM-based exploit synthesis with the Foundry testing suite,enabling the automated generation and validation of proof-of-concept (PoC)exploits. |
Zeke Xiao; Yuekang Li; Qin Wang; Shiping Chen; | arxiv-cs.CR | 2025-08-02 |
| 395 | Out-of-Context Abduction: LLMs Make Inferences About Procedural Data Leveraging Declarative Facts in Earlier Training Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Large language models (LLMs) are trained on large corpora, yet it is unclearwhether they can reason about the information present within their trainingdata. |
Sohaib Imran; Rob Lamb; Peter M. Atkinson; | arxiv-cs.CL | 2025-08-01 |
| 396 | Automated Type Annotation in Python Using Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 397 | Cross-Domain Web Information Extraction at Pinterest Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 398 | 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 |
WEI WU et. al. | Expert Syst. Appl. | 2025-08-01 |
| 399 | 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 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 |
| 400 | VAULT: Vigilant Adversarial Updates Via LLM-Driven Retrieval-Augmented Generation for NLI Summary Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 401 | 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 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 |
| 402 | Investigating Hallucination in Conversations for Low Resource Languages Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: While much research has focused onhallucinations in English, our study extends this investigation toconversational data in three languages: Hindi, Farsi, and Mandarin. We offer acomprehensive analysis of a dataset to examine both factual and linguisticerrors in these languages for GPT-3.5, GPT-4o, Llama-3.1, Gemma-2.0,DeepSeek-R1 and Qwen-3. |
AMIT DAS et. al. | arxiv-cs.CL | 2025-07-30 |
| 403 | Enabling Few-Shot Alzheimer’s Disease Diagnosis on Biomarker Data with Tabular LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 404 | Context-aware Rotary Position Embedding Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 405 | Automatic Classification of User Requirements from Online Feedback — A Replication Study Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 406 | Modelling Adjectival Modification Effects on Semantic Plausibility Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 407 | LLM-based Content Classification Approach for GitHub Repositories By The README Files Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 408 | 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 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 |
| 409 | FHSTP@EXIST 2025 Benchmark: Sexism Detection with Transparent Speech Concept Bottleneck Models Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 410 | 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 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 |
| 411 | Understanding Public Perception of Crime in Bangladesh: A Transformer-Based Approach with Explainability Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 412 | 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 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 |
| 413 | 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 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 |
| 414 | The Carbon Cost of Conversation, Sustainability in The Age of Language Models Summary Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 415 | Learning Neuro-symbolic Convergent Term Rewriting Systems Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 416 | Seeing Beyond Frames: Zero-Shot Pedestrian Intention Prediction with Raw Temporal Video and Multimodal Cues Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Here, we introduce BF-PIP (Beyond Frames Pedestrian IntentionPrediction), a zero-shot approach built upon Gemini 2.5 Pro. |
Pallavi Zambare; Venkata Nikhil Thanikella; Ying Liu; | arxiv-cs.CV | 2025-07-25 |
| 417 | ReCatcher: Towards LLMs Regression Testing for Code Generation Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 418 | Restoring Rhythm: Punctuation Restoration Using Transformer Models for Bangla, A Low-Resource Language Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 419 | Iwin Transformer: Hierarchical Vision Transformer Using Interleaved Windows Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 420 | 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 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 |
| 421 | Technical Report of TeleChat2, TeleChat2.5 and T1 Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 422 | DNT: A Deeply Normalized Transformer That Can Be Trained By Momentum SGD Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 423 | Write, Rank, or Rate: Comparing Methods for Studying Visualization Affordances Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 424 | 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 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 |
| 425 | Causal Graph Fuzzy LLMs: A First Introduction and Applications in Time Series Forecasting Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 426 | 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 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 |
| 427 | Can LLMs Write CI? A Study on Automatic Generation of GitHub Actions Configurations Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 428 | Confidence Optimization for Probabilistic Encoding Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 429 | Probing Information Distribution in Transformer Architectures Through Entropy Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 430 | The Lawyer That Never Thinks: Consistency and Fairness As Keys to Reliable AI Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 431 | 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 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 |
| 432 | EdgeInfinite: A Memory-Efficient Infinite-Context Transformer for Edge Devices Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 433 | Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference IF:5 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View 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 |
| 434 | 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 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 |
| 435 | Weak Links in LinkedIn: Enhancing Fake Profile Detection in The Age of LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 436 | When GPT Spills The Tea: Comprehensive Assessment of Knowledge File Leakage in GPTs Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 437 | 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 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 |
| 438 | FoldMoE: Efficient Long Sequence MoE Training Via Attention-MoE Pipelining Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 439 | Enhancing Goal-oriented Proactive Dialogue Systems Via Consistency Reflection and Correction Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 440 | Principled Understanding of Generalization for Generative Transformer Models in Arithmetic Reasoning Tasks Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 441 | INJONGO: A Multicultural Intent Detection and Slot-filling Dataset for 16 African Languages Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 442 | Automatic Evaluation for Text-to-image Generation: Task-decomposed Framework, Distilled Training, and Meta-evaluation Benchmark Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View 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 |
| 443 | Powerformer: Efficient and High-Accuracy Privacy-Preserving Language Model with Homomorphic Encryption Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 444 | GPT-4 As A Homework Tutor Can Improve Student Engagement and Learning Outcomes Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 445 | Efficient OpAmp Adaptation for Zoom Attention to Golden Contexts Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 446 | 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 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 |
| 447 | PaSa: An LLM Agent for Comprehensive Academic Paper Search IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce PaSa, an advanced Paper Search agent powered by large language models. |
YICHEN HE et. al. | acl | 2025-07-21 |
| 448 | Segment-Based Attention Masking for GPTs Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View 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 |
| 449 | 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 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 |
| 450 | Can Uniform Meaning Representation Help GPT-4 Translate from Indigenous Languages? Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 451 | PromptArmor: Simple Yet Effective Prompt Injection Defenses IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we presentPromptArmor, a simple yet effective defense against prompt injection attacks.Specifically, PromptArmor prompts an off-the-shelf LLM to detect and removepotential injected prompts from the input before the agent processes it. |
TIANNENG SHI et. al. | arxiv-cs.CR | 2025-07-20 |
| 452 | Language Models for Controllable DNA Sequence Design Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 453 | XL-DURel: Finetuning Sentence Transformers for Ordinal Word-in-Context Classification Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 454 | InTraVisTo: Inside Transformer Visualisation Tool Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 455 | AI-Assisted Fixes to Code Review Comments at Scale Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: As a baseline, we compare GPT-4o to our small and largeLlama models. |
CHANDRA MADDILA et. al. | arxiv-cs.SE | 2025-07-17 |
| 456 | Compact Vision Transformer By Reduction of Kernel Complexity Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 457 | 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 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 |
| 458 | ROSE: Transformer-Based Refactoring Recommendation for Architectural Smells Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 459 | PRISM: Distributed Inference for Foundation Models at Edge Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 460 | 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 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 |
| 461 | 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 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 |
| 462 | Cross-lingual Few-shot Learning for Persian Sentiment Analysis with Incremental Adaptation Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 463 | SIMCODE: A Benchmark for Natural Language to Ns-3 Network Simulation Code Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To facilitate systematic evaluation, we introduce SIMCODE,the first benchmark to evaluate LLMs’ ability to generate ns-3 simulation codefrom natural language. |
Tasnim Ahmed; Mirza Mohammad Azwad; Salimur Choudhury; | arxiv-cs.NI | 2025-07-15 |
| 464 | Addressing Data Imbalance in Transformer-Based Multi-Label Emotion Detection with Weighted Loss Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 465 | Abusive Text Transformation Using LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we aim to use LLMs to transformabusive text (tweets and reviews) featuring hate speech and swear words intonon-abusive text, while retaining the intent of the text. |
Rohitash Chandra; Jiyong Choi; | arxiv-cs.CL | 2025-07-14 |
| 466 | Pimba: A Processing-in-Memory Acceleration for Post-Transformer Large Language Model Serving Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 467 | From BERT to Qwen: Hate Detection Across Architectures Summary Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 468 | Player-Team Heterogeneous Interaction Graph Transformer for Soccer Outcome Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 469 | Language Models for Adult Service Website Text Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 470 | WebFAQ: A Multilingual Collection of Natural Q&A Datasets for Dense Retrieval Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 471 | CADmium: Fine-Tuning Code Language Models for Text-Driven Sequential CAD Design Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 472 | The Effects of Demographic Instructions on LLM Personas Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 473 | 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 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 |
| 474 | OPENXRD: A Comprehensive Benchmark and Enhancement Framework for LLM/MLLM XRD Question Answering Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 475 | 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 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 |
| 476 | TPP-SD: Accelerating Transformer Point Process Sampling with Speculative Decoding Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose TPP-SD, a novel approach that accelerates Transformer temporalpoint process (TPP) sampling by adapting speculative decoding (SD) techniquesfrom language models. |
Shukai Gong; Yiyang Fu; Fengyuan Ran; Quyu Kong; Feng Zhou; | arxiv-cs.LG | 2025-07-12 |
| 477 | Universal Approximation Theorem for A Single-Layer Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 478 | Intelligent Text Similarity Assessment Using Roberta with Integrated Chaotic Perturbation Optimization Techniques Related Papers Related Patents Related Grants Related Venues Related Experts View |
Esraa Hassan; Amira Samy Talaat; M. A. Elsabagh; | J. Big Data | 2025-07-11 |
| 479 | SynthEHR-Eviction: Enhancing Eviction SDoH Detection with LLM-Augmented Synthetic EHR Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Using this pipeline, we created the largestpublic eviction-related SDoH dataset to date, comprising 14 fine-grainedcategories. |
ZONGHAI YAO et. al. | arxiv-cs.CL | 2025-07-10 |
| 480 | 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 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 |
| 481 | Large Language Model for Extracting Complex Contract Information in Industrial Scenes Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 482 | ETT: Expanding The Long Context Understanding Capability of LLMs at Test-Time Related Papers Related Patents Related Grants Related Venues Related Experts View 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 |
| 483 | 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 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 |
| 484 | Divergent Realities: A Comparative Analysis of Human Expert Vs. Artificial Intelligence Based Generation and Evaluation of Treatment Plans in Dermatology Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Background: Evaluating AI-generated treatment plans is a key challenge as AIexpands beyond diagnostics, especially with new reasoning models. This studycompares plans from human … |
Dipayan Sengupta; Saumya Panda; | arxiv-cs.AI | 2025-07-08 |
| 485 | AI Generated Text Detection Using Instruction Fine-tuned Large Language and Transformer-Based Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work focuses on two primaryobjectives Task-A, which involves distinguishing human-written text frommachine-generated text, and Task-B, which attempts to identify the specific LLMmodel responsible for the generation. |
Chinnappa Guggilla; Budhaditya Roy; Trupti Ramdas Chavan; Abdul Rahman; Edward Bowen; | arxiv-cs.CL | 2025-07-07 |
| 486 | Signal or Noise? Evaluating Large Language Models in Resume Screening Across Contextual Variations and Human Expert Benchmarks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study investigates whether large language models (LLMs) exhibitconsistent behavior (signal) or random variation (noise) when screening resumesagainst job descriptions, and how their performance compares to human experts.Using controlled datasets, we tested three LLMs (Claude, GPT, and Gemini)across contexts (No Company, Firm1 [MNC], Firm2 [Startup], Reduced Context)with identical and randomized resumes, benchmarked against three humanrecruitment experts. |
Aryan Varshney; Venkat Ram Reddy Ganuthula; | arxiv-cs.CL | 2025-07-07 |
| 487 | Performance Evaluation of General Purpose Large Language Models for Basic Linear Algebra Subprograms Code Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We use two LLMsprovided by OpenAI: GPT-4.1, a Generative Pre-trained Transformer (GPT) model,and o4-mini, one of the o-series of Reasoning models. |
Daichi Mukunoki; Shun-ichiro Hayashi; Tetsuya Hoshino; Takahiro Katagiri; | arxiv-cs.LG | 2025-07-07 |
| 488 | Assessing The Capabilities and Limitations of FinGPT Model in Financial NLP Applications Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work evaluates FinGPT, a financial domain-specific language model,across six key natural language processing (NLP) tasks: Sentiment Analysis,Text Classification, Named Entity Recognition, Financial Question Answering,Text Summarization, and Stock Movement Prediction. |
Prudence Djagba; Chimezie A. Odinakachukwu; | arxiv-cs.CL | 2025-07-06 |
| 489 | MedicalBERT: Enhancing Biomedical Natural Language Processing Using Pretrained BERT-based Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work alsounderscoresthe potential of leveraging pretrained BERT models for medicalNLP tasks,demonstrating the effectiveness of transfer learning techniques incapturingdomain-specific information. |
K. SAHIT REDDY et. al. | arxiv-cs.CL | 2025-07-05 |
| 490 | VLAI: A RoBERTa-Based Model for Automated Vulnerability Severity Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents VLAI, a transformer-based model that predicts softwarevulnerability severity levels directly from text descriptions. |
Cédric Bonhomme; Alexandre Dulaunoy; | arxiv-cs.CR | 2025-07-04 |
| 491 | QFFN-BERT: An Empirical Study of Depth, Performance, and Data Efficiency in Hybrid Quantum-Classical Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In thiswork, we introduce QFFN-BERT, a hybrid quantum-classical transformer where thefeedforward network (FFN) modules of a compact BERT variant are replaced byPQC-based layers. |
Pilsung Kang; | arxiv-cs.CL | 2025-07-03 |
| 492 | Transformers Don’t Need LayerNorm at Inference Time: Scaling LayerNorm Removal to GPT-2 XL and The Implications for Mechanistic Interpretability Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Our work clarifies the role of LN layers in language modeling, showingthat GPT-2-class models can function without LN layers. |
Luca Baroni; Galvin Khara; Joachim Schaeffer; Marat Subkhankulov; Stefan Heimersheim; | arxiv-cs.LG | 2025-07-03 |
| 493 | Exploring LLM-generated Culture-specific Affective Human-Robot Tactile Interaction Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: As large language models (LLMs) become increasingly integrated into robotic systems, their potential to generate socially and culturally appropriate affective touch remains … |
Qiaoqiao Ren; Tony Belpaeme; | ArXiv | 2025-07-02 |
| 494 | How Well Does GPT-4o Understand Vision? Evaluating Multimodal Foundation Models on Standard Computer Vision Tasks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we benchmark the performance of popularmultimodal foundation models (GPT-4o, o4-mini, Gemini 1.5 Pro and Gemini 2.0Flash, Claude 3.5 Sonnet, Qwen2-VL, Llama 3.2) on standard computer visiontasks (semantic segmentation, object detection, image classification, depth andsurface normal prediction) using established datasets (e.g., COCO, ImageNet andits variants, etc). |
RAHUL RAMACHANDRAN et. al. | arxiv-cs.CV | 2025-07-02 |
| 495 | Stylometry Recognizes Human and LLM-generated Texts in Short Samples Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The paper explores stylometry as a method to distinguish between textscreated by Large Language Models (LLMs) and humans, addressing issues of modelattribution, intellectual property, and ethical AI use. |
Karol Przystalski; Jan K. Argasiński; Iwona Grabska-Gradzińska; Jeremi K. Ochab; | arxiv-cs.CL | 2025-07-01 |
| 496 | Evaluating Large Language Models for Multimodal Simulated Ophthalmic Decision-Making in Diabetic Retinopathy and Glaucoma Screening Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We conducted a retrospectivediagnostic validation study using 300 annotated fundus images. |
CINDY LIE TABUSE et. al. | arxiv-cs.CL | 2025-07-01 |
| 497 | Pitfalls of Evaluating Language Models with Open Benchmarks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Our findingsunderscore three key insights: \ca high leaderboard performance on openbenchmarks may not always reflect real-world effectiveness; \cb private ordynamic benchmarks must complement open evaluations to safeguard integrity; and\cc a fundamental reevaluation of current benchmarking practices is essentialto ensure robust and trustworthy LM assessments. |
Md. Najib Hasan; Mohammad Fakhruddin Babar; Souvika Sarkar; Monowar Hasan; Santu Karmaker; | arxiv-cs.CL | 2025-07-01 |
| 498 | GAIus: Combining Genai with Legal Clauses Retrieval for Knowledge-based Assistant Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper we discuss the capability of large language models to basetheir answer and provide proper references when dealing with legal matters ofnon-english and non-chinese speaking country. |
Michał Matak; Jarosław A. Chudziak; | arxiv-cs.CL | 2025-07-01 |
| 499 | Leveraging Textual Description and Structured Data for Estimating Crash Risks of Traffic Violation: A Multimodal Learning Approach Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This study introduces a novel methodology that integrates both structured data and unstructured violation descriptions, addressing a critical gap in current crash risk estimation … |
Zihao Li; Chaolun Ma; Yang Zhou; Dominique Lord; Yunlong Zhang; | IEEE Transactions on Intelligent Transportation Systems | 2025-07-01 |
| 500 | Large Language Models Don’t Make Sense of Word Problems. A Scoping Review from A Mathematics Education Perspective Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In sum, we argue based on all three aspects that LLMs havemastered a superficial solution process but do not make sense of word problems,which potentially limits their value as instructional tools in mathematicsclassrooms. |
Anselm R. Strohmaier; Wim Van Dooren; Kathrin Seßler; Brian Greer; Lieven Verschaffel; | arxiv-cs.CL | 2025-06-30 |
| 501 | Robustness of Misinformation Classification Systems to Adversarial Examples Through BeamAttack Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We extend BeamAttack, an adversarial attack algorithm designed to evaluatethe robustness of text classification systems through word-level modificationsguided by beam search. |
Arnisa Fazla; Lucas Krauter; David Guzman Piedrahita; Andrianos Michail; | arxiv-cs.CL | 2025-06-30 |
| 502 | PBa-LLM: Privacy- and Bias-aware NLP Using Named-Entity Recognition (NER) Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Due to these concerns,this work explores the use of Named- Entity Recognition (NER) to facilitate theprivacy-preserving training (or adaptation) of LLMs. We propose a frameworkthat uses NER technologies to anonymize sensitive information in text data,such as personal identities or geographic locations. |
GONZALO MANCERA et. al. | arxiv-cs.CL | 2025-06-30 |
| 503 | User Behavior Prediction As A Generic, Robust, Scalable, and Low-Cost Evaluation Strategy for Estimating Generalization in LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Instead, we propose user behavior prediction, also a key aspectof personalization, as a theoretically sound, scalable, and robust alternative.We introduce a novel framework for this approach and test it on movie and musicrecommendation datasets for GPT-4o, GPT-4o-mini, and Llama-3.1-8B-Instruct. |
Sougata Saha; Monojit Choudhury; | arxiv-cs.CL | 2025-06-30 |
| 504 | Examining Reject Relations in Stimulus Equivalence Simulations Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study investigates the role of rejectrelations in the acquisition of stimulus equivalence using computationalmodels. |
Alexis Carrillo; Asieh Abolpour Mofrad; Anis Yazidi; Moises Betancort; | arxiv-cs.LG | 2025-06-30 |
| 505 | Advancing Learnable Multi-Agent Pathfinding Solvers with Active Fine-Tuning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To this end, decentralizedsuboptimal MAPF solvers that leverage machine learning have come on stage.Building on the success of the recently introduced MAPF-GPT, a pure imitationlearning solver, we introduce MAPF-GPT-DDG. |
Anton Andreychuk; Konstantin Yakovlev; Aleksandr Panov; Alexey Skrynnik; | arxiv-cs.AI | 2025-06-30 |
| 506 | SketchMind: A Multi-Agent Cognitive Framework for Assessing Student-Drawn Scientific Sketches Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To address theselimitations, we present SketchMind, a cognitively grounded, multi-agentframework for evaluating and improving student-drawn scientific sketches.SketchMind comprises modular agents responsible for rubric parsing, sketchperception, cognitive alignment, and iterative feedback with sketchmodification, enabling personalized and transparent evaluation. |
Ehsan Latif; Zirak Khan; Xiaoming Zhai; | arxiv-cs.HC | 2025-06-29 |
| 507 | Measuring How LLMs Internalize Human Psychological Concepts: A Preliminary Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Large Language Models (LLMs) such as ChatGPT have shown remarkable abilitiesin producing human-like text. |
Hiro Taiyo Hamada; Ippei Fujisawa; Genji Kawakita; Yuki Yamada; | arxiv-cs.LG | 2025-06-28 |
| 508 | Residual Matrix Transformers: Scaling The Size of The Residual Stream Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We consider changing the mechanismfor retrieving and storing information in the residual stream, and replace theresidual stream of the transformer with an outer product memory matrix(Kohonen, 1972, Anderson, 1972). |
Brian Mak; Jeffrey Flanigan; | arxiv-cs.LG | 2025-06-27 |
| 509 | Assessing The Feasibility of Large Language Models for Detecting Micro-behaviors in Team Interactions During Space Missions Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We explore the feasibility of large language models (LLMs) in detectingsubtle expressions of micro-behaviors in team conversations using transcriptscollected during simulated space missions. |
Ankush Raut; Projna Paromita; Sydney Begerowski; Suzanne Bell; Theodora Chaspari; | arxiv-cs.CL | 2025-06-27 |
| 510 | Identifying A Circuit for Verb Conjugation in GPT-2 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: I implement a procedure to isolate and interpret the sub-network (orcircuit) responsible for subject-verb agreement in GPT-2 Small. |
David Demitri Africa; | arxiv-cs.CL | 2025-06-27 |
| 511 | HLTCOE at LiveRAG: GPT-Researcher Using ColBERT Retrieval Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The HLTCOE LiveRAG submission utilized the GPT-researcher framework forresearching the context of the question, filtering the returned results, andgenerating the final answer. |
Kevin Duh; Eugene Yang; Orion Weller; Andrew Yates; Dawn Lawrie; | arxiv-cs.IR | 2025-06-27 |
| 512 | Offensive Language Detection on Social Media Using XLNet Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Deep learning models, particularly those usingtransfer learning, have demonstrated significant success in understandingnatural language through large-scale pretraining. In this study, we propose anautomatic offensive language detection model based on XLNet, a generalizedautoregressive pretraining method, and compare its performance with BERT(Bidirectional Encoder Representations from Transformers), which is a widelyused baseline in natural language processing (NLP). |
Reem Alothman; Hafida Benhidour; Said Kerrache; | arxiv-cs.CL | 2025-06-26 |
| 513 | Fine-Tuning and Prompt Engineering of LLMs, for The Creation of Multi-Agent AI for Addressing Sustainable Protein Production Challenges Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we present a proof-of-concept multi-agentArtificial Intelligence (AI) framework designed to support sustainable proteinproduction research, with an initial focus on microbial protein sources. |
ALEXANDER D. KALIAN et. al. | arxiv-cs.AI | 2025-06-25 |
| 514 | A Bayesian Model Selection Criterion for Selecting Pretraining Checkpoints Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce a Bayesian model selection criterion, called the downstream free energy, which quantifies a checkpoint’s adaptability by measuring the concentration of nearby favorable parameters for a downstream task. |
Michael Munn; Susan Wei; | icml | 2025-06-25 |
| 515 | The Lock-in Hypothesis: Stagnation By Algorithm Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The training and deployment of large language models (LLMs) create a feedback loop with human users: models learn human beliefs from data, reinforce these beliefs with generated content, reabsorb the reinforced beliefs, and feed them back to users again and again. |
Tianyi Qiu; Zhonghao He; Tejasveer Chugh; Max Kleiman-Weiner; | icml | 2025-06-25 |
| 516 | Consensus Is All You Get: The Role of Attention in Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper we provide a rigorous, mathematical analysis of the asymptotic properties of attention in transformers. |
Álvaro Rodríguez Abella; João Pedro Silvestre; Paulo Tabuada; | icml | 2025-06-25 |
| 517 | PDE-Transformer: Efficient and Versatile Transformers for Physics Simulations Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce PDE-Transformer, an improved transformer-based architecture for surrogate modeling of physics simulations on regular grids. |
Benjamin Holzschuh; Qiang Liu; Georg Kohl; Nils Thuerey; | icml | 2025-06-25 |
| 518 | On Exact Bit-level Reversible Transformers Without Changing Architecture Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work we present the BDIA-transformer, which is an exact bit-level reversible transformer that uses an unchanged standard architecture for inference. |
Guoqiang Zhang; JP Lewis; W. Bastiaan Kleijn; | icml | 2025-06-25 |
| 519 | Sorbet: A Neuromorphic Hardware-Compatible Transformer-Based Spiking Language Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, key operations like softmax and layer normalization (LN) are difficult to implement on neuromorphic hardware, and many of these early works sidestepped them. To address these challenges, we introduce Sorbet, a transformer-based spiking language model that is more neuromorphic hardware-compatible. |
Kaiwen Tang; Zhanglu Yan; Weng-Fai Wong; | icml | 2025-06-25 |
| 520 | An Efficient Private GPT Never Autoregressively Decodes Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To accelerate secure inference, this study proposes a public decoding and secure verification approach that utilizes public GPT models, motivated by the observation that securely decoding one and multiple tokens takes a similar latency. |
ZHENGYI LI et. al. | icml | 2025-06-25 |
| 521 | MAS-GPT: Training LLMs to Build LLM-based Multi-Agent Systems IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we simplify the process of building an MAS by reframing it as a generative language task, where the input is a user query and the output is a corresponding MAS. |
RUI YE et. al. | icml | 2025-06-25 |
| 522 | Teaching Transformers Causal Reasoning Through Axiomatic Training Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Since interventional data is costly to generate, we study to what extent an agent can learn causal reasoning from passive data. |
ANIKET VASHISHTHA et. al. | icml | 2025-06-25 |
| 523 | A Causal World Model Underlying Next Token Prediction: Exploring GPT in A Controlled Environment Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Are generative pre-trained transformer (GPT) models, trained only to predict the next token, implicitly learning a world model from which sequences are generated one token at a time? We address this question by deriving a causal interpretation of the attention mechanism in GPT and presenting a causal world model that arises from this interpretation. |
Raanan Yehezkel Rohekar; Yaniv Gurwicz; Sungduk Yu; Estelle Aflalo; Vasudev Lal; | icml | 2025-06-25 |
| 524 | Attention-Only Transformers Via Unrolled Subspace Denoising Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Despite the popularity of transformers in practice, their architectures are empirically designed and neither mathematically justified nor interpretable. Moreover, as indicated by … |
PENG WANG et. al. | icml | 2025-06-25 |
| 525 | GraphGPT: Generative Pre-trained Graph Eulerian Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce *GraphGPT*, a novel self-supervised *generative pre-trained* model for graph learning based on the *Graph Eulerian Transformer* (**GET**). |
QIFANG ZHAO et. al. | icml | 2025-06-25 |
| 526 | AdaSplash: Adaptive Sparse Flash Attention Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose AdaSplash, which combines the efficiency of GPU-optimized algorithms with the sparsity benefits of $\alpha$-entmax. |
Nuno Gonçalves; Marcos V Treviso; Andre Martins; | icml | 2025-06-25 |
| 527 | FlexTok: Resampling Images Into 1D Token Sequences of Flexible Length IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce FlexTok, a tokenizer that projects 2D images into variable-length, ordered 1D token sequences. |
ROMAN BACHMANN et. al. | icml | 2025-06-25 |
| 528 | A Lens Into Interpretable Transformer Mistakes Via Semantic Dependency Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we investigate the role of semantic dependencies in answering questions for transformer models, which is achieved by analyzing how token values shift in response to changes in semantics. |
Ruo-Jing Dong; Yu Yao; Bo Han; Tongliang Liu; | icml | 2025-06-25 |
| 529 | In-Context Reinforcement Learning From Suboptimal Historical Data Related Papers Related Patents Related Grants Related Venues Related Experts View 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; | icml | 2025-06-25 |
| 530 | PENCIL: Long Thoughts with Short Memory Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce PENCIL, which incorporates a novel reduction mechanism into the autoregressive generation process that recursively clean up intermediate thoughts based on patterns learned from training. |
Chenxiao Yang; Nathan Srebro; David McAllester; Zhiyuan Li; | icml | 2025-06-25 |
| 531 | CodeSteer: Symbolic-Augmented Language Models Via Code/Text Guidance Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce CodeSteer, an effective method for guiding LLM code/text generation. |
Yongchao Chen; Yilun Hao; Yueying Liu; Yang Zhang; Chuchu Fan; | icml | 2025-06-25 |
| 532 | The Underlying Structures of Self-attention: Symmetry, Directionality, and Emergent Dynamics in Transformer Training Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present a mathematical framework to analyze self-attention matrices by deriving the structures governing their weight updates. |
Matteo Saponati; Pascal Josef Sager; Pau Vilimelis Aceituno; Thilo Stadelmann; Benjamin F Grewe; | icml | 2025-06-25 |
| 533 | Commander-GPT: Dividing and Routing for Multimodal Sarcasm Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose Commander-GPT, a modular decisionrouting framework inspired by military command theory. |
Yazhou Zhang; Chunwang Zou; Bo Wang; Jing Qin; | arxiv-cs.AI | 2025-06-24 |
| 534 | Leveraging Large Language Models for Information Verification — An Engineering Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: For the ACMMM25 challenge, we present a practical engineering approach tomultimedia news source verification, utilizing Large Language Models (LLMs)like GPT-4o as the backbone of our pipeline. |
NGUYEN NANG HUNG et. al. | arxiv-cs.LG | 2025-06-23 |
| 535 | Spiritual-LLM : Gita Inspired Mental Health Therapy In The Era of LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present the GITes (Gita Integrated Therapy for Emotional Support) dataset,which enhances the existing ExTES mental health dataset by including 10,729spiritually guided responses generated by GPT-4o and evaluated by domainexperts. |
Janak Kapuriya; Aman Singh; Jainendra Shukla; Rajiv Ratn Shah; | arxiv-cs.AI | 2025-06-23 |
| 536 | Evaluating Causal Explanation in Medical Reports with LLM-Based and Human-Aligned Metrics Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study investigates how accurately different evaluation metrics capturethe quality of causal explanations in automatically generated diagnosticreports. |
Yousang Cho; Key-Sun Choi; | arxiv-cs.CL | 2025-06-23 |
| 537 | Security Assessment of DeepSeek and GPT Series Models Against Jailbreak Attacks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: While proprietary models like GPT-4 have undergone extensiveevaluation, the robustness of emerging open-source alternatives such asDeepSeek remains largely underexplored, despite their growing adoption inreal-world applications. In this paper, we present the first systematicjailbreak evaluation of DeepSeek-series models, comparing them with GPT-3.5 andGPT-4 using the HarmBench benchmark. |
Xiaodong Wu; Xiangman Li; Jianbing Ni; | arxiv-cs.CR | 2025-06-23 |
| 538 | Detecting Code Vulnerabilities Using LLMs Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Large language models (LLMs) have emerged as a promising tool for detecting code vulnerabilities, potentially offering advantages over traditional rule-based methods. This paper … |
LARRY HUYNH et. al. | 2025 55th Annual IEEE/IFIP International Conference on … | 2025-06-23 |
| 539 | The Anatomy of Speech Persuasion: Linguistic Shifts in LLM-Modified Speeches Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Our contributions include a novel methodology and an interpretabletextual feature set integrating rhetorical devices and discourse markers. |
Alisa Barkar; Mathieu Chollet; Matthieu Labeau; Beatrice Biancardi; Chloe Clavel; | arxiv-cs.CL | 2025-06-23 |
| 540 | SWE-GPT: A Process-Centric Language Model for Automated Software Improvement Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Large language models (LLMs) have demonstrated remarkable performance in code generation, significantly enhancing the coding efficiency of developers. Recent advancements in … |
YINGWEI MA et. al. | Proc. ACM Softw. Eng. | 2025-06-22 |
| 541 | Can AI Take A Joke—Or Make One? A Study of Humor Generation and Recognition in LLMs Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Knowing when to joke—and when not to—is a subtle skill often missing in large language models (LLMs). This study examines how well LLMs generate and recognize humor in emotionally … |
Kexin Quan; Pavithra Ramakrishnan; Jessie Chin; | Proceedings of the 2025 Conference on Creativity and … | 2025-06-22 |
| 542 | Auto-Regressive Surface Cutting Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce SeamGPT, an auto-regressive modelthat generates cutting seams by mimicking professional workflows. |
YANG LI et. al. | arxiv-cs.GR | 2025-06-22 |
| 543 | ShareGPT-4o-Image: Aligning Multimodal Models with GPT-4o-Level Image Generation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Recent advances in multimodal generative models have unlocked photorealistic,instruction-aligned image generation, yet leading systems like GPT-4o-Imageremain proprietary and inaccessible. To democratize these capabilities, wepresent ShareGPT-4o-Image, the first dataset comprising 45K text-to-image and46K text-and-image-to-image data, all synthesized using GPT-4o’s imagegeneration capabilities for distilling its advanced image generation abilities.Leveraging this dataset, we develop Janus-4o, a multimodal large language modelcapable of both text-to-image and text-and-image-to-image generation. |
JUNYING CHEN et. al. | arxiv-cs.CV | 2025-06-22 |
| 544 | Log-Normal Multiplicative Dynamics for Stable Low-Precision Training of Large Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Studies in neuroscience have shown that biological synapses follow alog-normal distribution whose transitioning can be explained by noisymultiplicative dynamics. |
Keigo Nishida; Eren Mehmet Kıral; Kenichi Bannai; Mohammad Emtiyaz Khan; Thomas Möllenhoff; | arxiv-cs.LG | 2025-06-21 |
| 545 | Actionable Interpretability Via Causal Hypergraphs: Unravelling Batch Size Effects in Deep Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Our analysis reveals that smaller batch sizescausally enhance generalisation through increased stochasticity and flatterminima, offering actionable interpretability to guide training strategies indeep learning. |
Zhongtian Sun; Anoushka Harit; Pietro Lio; | arxiv-cs.LG | 2025-06-21 |
| 546 | Leveraging LLMs to Assess Tutor Moves in Real-Life Dialogues: A Feasibility Study Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We analyze 50randomly selected transcripts of college-student remote tutors assisting middleschool students in mathematics. |
DANIELLE R. THOMAS et. al. | arxiv-cs.CL | 2025-06-20 |
| 547 | FRED: A Wafer-scale Fabric for 3D Parallel DNN Training Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Wafer-scale systems are an emerging technology that tightly integrates high-end accelerator chiplets with high-speed wafer-scale interconnects, enabling low-latency and … |
Saeed Rashidi; William Won; S. Srinivasan; Puneet Gupta; Tushar Krishna; | Proceedings of the 52nd Annual International Symposium on … | 2025-06-20 |
| 548 | Trans${^2}$-CBCT: A Dual-Transformer Framework for Sparse-View CBCT Reconstruction Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We adapt TransUNet to CBCT by combining multi-scale features,querying view-specific features per 3D point, and adding a lightweightattenuation-prediction head. This yields Trans-CBCT, which surpasses priorbaselines by 1.17 dB PSNR and 0.0163 SSIM on the LUNA16 dataset with six views.Second, we introduce a neighbor-aware Point Transformer to enforce volumetriccoherence. |
Minmin Yang; Huantao Ren; Senem Velipasalar; | arxiv-cs.CV | 2025-06-20 |
| 549 | Do We Talk to Robots Like Therapists, and Do They Respond Accordingly? Language Alignment in AI Emotional Support Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study investigates whether theconcerns shared with a robot align with those shared in human-to-human (H2H)therapy sessions, and whether robot responses semantically mirror those ofhuman therapists. |
Sophie Chiang; Guy Laban; Hatice Gunes; | arxiv-cs.HC | 2025-06-19 |
| 550 | JETHICS: Japanese Ethics Understanding Evaluation Dataset Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose JETHICS, a Japanese dataset for evaluating ethicsunderstanding of AI models. |
Masashi Takeshita; Rafal Rzepka; | arxiv-cs.CL | 2025-06-19 |
| 551 | Can GPT-4o Evaluate Usability Like Human Experts? A Comparative Study on Issue Identification in Heuristic Evaluation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, prior researchhas not investigated GPT-4o’s performance in heuristic evaluation compared toHCI experts in web-based systems. In this context, this study aims to comparethe results of a heuristic evaluation performed by GPT-4o and human experts. |
GUILHERME GUERINO et. al. | arxiv-cs.HC | 2025-06-19 |
| 552 | Optimizing Web-Based AI Query Retrieval with GPT Integration in LangChain A CoT-Enhanced Prompt Engineering Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work proposes a novel approach to enhancing remote learning retrieval by integrating GPT-based models within the LangChain framework. |
Wenqi Guan; Yang Fang; | arxiv-cs.HC | 2025-06-18 |
| 553 | I Know Which LLM Wrote Your Code Last Summer: LLM Generated Code Stylometry for Authorship Attribution Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents the first systematic study of LLMauthorship attribution for C programs. |
TAMAS BISZTRAY et. al. | arxiv-cs.LG | 2025-06-18 |
| 554 | A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study analyzes various proprietary and open-source LLMs for a single-label, multi-class text classification task focused on the SDGs. |
ANDREA CADEDDU et. al. | arxiv-cs.CL | 2025-06-18 |
| 555 | LLM Vs. SAST: A Technical Analysis on Detecting Coding Bugs of GPT4-Advanced Data Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper investigates the efficacy of GPT-4 in identifying software vulnerabilities compared to traditional Static Application Security Testing (SAST) tools. |
Madjid G. Tehrani; Eldar Sultanow; William J. Buchanan; Mahkame Houmani; Christel H. Djaha Fodja; | arxiv-cs.CR | 2025-06-18 |
| 556 | Scaling Intelligence: Designing Data Centers for Next-Gen Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce and evaluateFullFlat network architectures, which provide uniform high-bandwidth,low-latency connectivity between all nodes, and demonstrate theirtransformative impact on performance and scalability. |
Jesmin Jahan Tithi; Hanjiang Wu; Avishaii Abuhatzera; Fabrizio Petrini; | arxiv-cs.AR | 2025-06-17 |
| 557 | Enhancement Report Approval Prediction: A Comparative Study of Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Enhancement reports (ERs) serve as a critical communication channel between users and developers, capturing valuable suggestions for software improvement. |
Haosheng Zuo; Feifei Niu; Chuanyi Li; | arxiv-cs.SE | 2025-06-17 |
| 558 | Toward A Graph Foundation Model: Pre-Training Transformers With Random Walks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper describes an approach toward a graph foundation model that is pre-trained with diverse graph datasets by adapting the Transformer backbone. |
Ziyuan Tang; Jie Chen; | arxiv-cs.LG | 2025-06-16 |
| 559 | Detecting Hard-Coded Credentials in Software Repositories Via LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We have made all source code and data publicly available to facilitate the reproduction of all results presented in this paper. |
Chidera Biringa; Gokhan Kul; | arxiv-cs.CR | 2025-06-16 |
| 560 | GITO: Graph-Informed Transformer Operator for Learning Complex Partial Differential Equations Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present a novel graph-informed transformer operator (GITO) architecturefor learning complex partial differential equation systems defined on irregulargeometries and non-uniform meshes. |
Milad Ramezankhani; Janak M. Patel; Anirudh Deodhar; Dagnachew Birru; | arxiv-cs.LG | 2025-06-16 |
| 561 | Antibody Foundational Model : Ab-RoBERTa Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we introduce Ab-RoBERTa, a RoBERTa-based antibody-specific LLM, which is publicly available at https://huggingface.co/mogam-ai/Ab-RoBERTa. |
Eunna Huh; Hyeonsu Lee; Hyunjin Shin; | arxiv-cs.LG | 2025-06-15 |
| 562 | Missing The Human Touch? A Computational Stylometry Analysis of GPT-4 Translations of Online Chinese Literature Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Computational stylometry analysis shows that GPT-4 translations closely align with human translations in lexical, syntactic, and content features, suggesting that LLMs might replicate the ‘human touch’ in literary translation style. |
Xiaofang Yao; Yong-Bin Kang; Anthony McCosker; | arxiv-cs.CL | 2025-06-15 |
| 563 | Mastering Da Vinci Code: A Comparative Study of Transformer, LLM, and PPO-based Agents Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The Da Vinci Code, a game of logical deduction and imperfect information, presents unique challenges for artificial intelligence, demanding nuanced reasoning beyond simple pattern recognition. This paper investigates the efficacy of various AI paradigms in mastering this game. |
LeCheng Zhang; Yuanshi Wang; Haotian Shen; Xujie Wang; | arxiv-cs.AI | 2025-06-15 |
| 564 | Transforming Chatbot Text: A Sequence-to-Sequence Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we adopt a novel strategy to adversarially transform GPT-generated text using sequence-to-sequence (Seq2Seq) models, with the goal of making the text more human-like. |
Natesh Reddy; Mark Stamp; | arxiv-cs.CL | 2025-06-15 |
| 565 | Exploring Cultural Variations in Moral Judgments with Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we examine whether LLMs can mirror variations in moral attitudes reported by two major cross-cultural surveys: the World Values Survey and the PEW Research Center’s Global Attitudes Survey. |
Hadi Mohammadi; Efthymia Papadopoulou; Yasmeen F. S. S. Meijer; Ayoub Bagheri; | arxiv-cs.CL | 2025-06-14 |
| 566 | Identifying Helpful Context for LLM-based Vulnerability Repair: A Preliminary Study Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper investigates the performance of GPT-4o in repairing Java vulnerabilities from a widely used dataset (Vul4J), exploring how different contextual information affects automated vulnerability repair (AVR) capabilities. |
Gábor Antal; Bence Bogenfürst; Rudolf Ferenc; Péter Hegedűs; | arxiv-cs.SE | 2025-06-13 |
| 567 | Attention-based Adversarial Robust Distillation in Radio Signal Classifications for Low-Power IoT Devices Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We have shown that transformer-based radio signal classification is vulnerable to imperceptible and carefully crafted attacks called adversarial examples. Therefore, we propose a defense system against adversarial examples in transformer-based modulation classifications. |
LU ZHANG et. al. | arxiv-cs.LG | 2025-06-13 |
| 568 | GeistBERT: Breathing Life Into German NLP Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Advances in transformer-based language models have highlighted the benefitsof language-specific pre-training on high-quality corpora. In this context,German NLP stands to gain … |
Raphael Scheible-Schmitt; Johann Frei; | arxiv-cs.CL | 2025-06-13 |
| 569 | Leveraging GPT-4 for Vulnerability-Witnessing Unit Test Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To help developers and security experts, this paper explores the automatic unit test generation capability of one of the most widely used large language models, GPT-4, from the perspective of vulnerabilities. |
Gábor Antal; Dénes Bán; Martin Isztin; Rudolf Ferenc; Péter Hegedűs; | arxiv-cs.SE | 2025-06-13 |
| 570 | NeuralNexus at BEA 2025 Shared Task: Retrieval-Augmented Prompting for Mistake Identification in AI Tutors Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper presents our system for Track 1: Mistake Identification in the BEA 2025 Shared Task on Pedagogical Ability Assessment of AI-powered Tutors. |
Numaan Naeem; Sarfraz Ahmad; Momina Ahsan; Hasan Iqbal; | arxiv-cs.CL | 2025-06-12 |
| 571 | Enhancing Mathematical Reasoning in GPT-J Through Topic-Aware Prompt Engineering Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This study evaluates the effectiveness of three prompting strategies: standard prompting, chain-of-thought (CoT) prompting, and informed CoT prompting on the performance of the … |
Lev Sukherman; Y. Folajimi; | Adjunct Proceedings of the 33rd ACM Conference on User … | 2025-06-12 |
| 572 | Large Language Models for Toxic Language Detection in Low-Resource Balkan Languages Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we evaluate how large language models handle toxic comments in Serbian, Croatian, and Bosnian, languages with limited labeled data. |
Amel Muminovic; Amela Kadric Muminovic; | arxiv-cs.CL | 2025-06-11 |
| 573 | The NordDRG AI Benchmark for Large Language Models Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Large language models (LLMs) are being piloted for clinical coding anddecision support, yet no open benchmark targets the hospital-funding layerwhere Diagnosis-Related Groups … |
Tapio Pitkäranta; | arxiv-cs.AI | 2025-06-11 |
| 574 | Check My Work?: Measuring Sycophancy in A Simulated Educational Context Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study examines how user-provided suggestions affect Large Language Models (LLMs) in a simulated educational context, where sycophancy poses significant risks. |
Chuck Arvin; | arxiv-cs.CL | 2025-06-11 |
| 575 | Gender Bias in English-to-Greek Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Additionally, we explore the potential of prompted GPT-4o as a bias mitigation tool that provides both gender-explicit and gender-neutral alternatives when necessary. To achieve this, we introduce GendEL, a manually crafted bilingual dataset of 240 gender-ambiguous and unambiguous sentences that feature stereotypical occupational nouns and adjectives. |
Eleni Gkovedarou; Joke Daems; Luna De Bruyne; | arxiv-cs.CL | 2025-06-11 |
| 576 | A Novel Lightweight Transformer with Edge-Aware Fusion for Remote Sensing Image Captioning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Transformer-based models have achieved strong performance in remote sensing image captioning by capturing long-range dependencies and contextual information. |
Swadhin Das; Divyansh Mundra; Priyanshu Dayal; Raksha Sharma; | arxiv-cs.CV | 2025-06-11 |
| 577 | Multilingual Hate Speech Detection in Social Media Using Translation-Based Approaches with Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: While hate speech detection has been extensively studied in languages like English and Spanish, Urdu remains underexplored, especially using translation-based approaches. To address this gap, we introduce a trilingual dataset of 10,193 tweets in English (3,834 samples), Urdu (3,197 samples), and Spanish (3,162 samples), collected via keyword filtering, with a balanced distribution of 4,849 Hateful and 5,344 Not-Hateful labels. |
MUHAMMAD USMAN et. al. | arxiv-cs.CL | 2025-06-09 |
| 578 | Swiss Parliaments Corpus Re-Imagined (SPC_R): Enhanced Transcription with RAG-based Correction and Predicted BLEU Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a new long-form release of the Swiss Parliaments Corpus, converting entire multi-hour Swiss German debate sessions (each aligned with the official session protocols) into high-quality speech-text pairs. |
Vincenzo Timmel; Manfred Vogel; Daniel Perruchoud; Reza Kakooee; | arxiv-cs.CL | 2025-06-09 |
| 579 | Evaluating Visual Mathematics in Multimodal LLMs: A Multilingual Benchmark Based on The Kangaroo Tests Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper analyzes the development and evaluation of MLLMs for mathematical problem solving, focusing on diagrams, multilingual text, and symbolic notation. |
ARNAU IGUALDE SÁEZ et. al. | arxiv-cs.AI | 2025-06-09 |
| 580 | Vuyko Mistral: Adapting LLMs for Low-Resource Dialectal Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper we introduce the first effort to adapt large language models (LLMs) to the Ukrainian dialect (in our case Hutsul), a low-resource and morphologically complex dialect spoken in the Carpathian Highlands. |
Roman Kyslyi; Yuliia Maksymiuk; Ihor Pysmennyi; | arxiv-cs.CL | 2025-06-09 |
| 581 | Prompt to Protection: A Comparative Study of Multimodal LLMs in Construction Hazard Recognition Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study offers actionable insights into the integration of prompt engineering and LLMs for practical hazard recognition, contributing to the development of more reliable AI-assisted safety systems. |
Nishi Chaudhary; S M Jamil Uddin; Sathvik Sharath Chandra; Anto Ovid; Alex Albert; | arxiv-cs.CV | 2025-06-09 |
| 582 | JavelinGuard: Low-Cost Transformer Architectures for LLM Security Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present JavelinGuard, a suite of low-cost, high-performance model architectures designed for detecting malicious intent in Large Language Model (LLM) interactions, optimized specifically for production deployment. |
Yash Datta; Sharath Rajasekar; | arxiv-cs.LG | 2025-06-08 |
| 583 | Exploring Effective Strategies for Building A Customised GPT Agent for Coding Classroom Dialogues Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study investigates effective strategies for developing a customised GPT agent to code classroom dialogue. |
Luwei Bai; Dongkeun Han; Sara Hennessy; | arxiv-cs.AI | 2025-06-08 |
| 584 | D^2iT: Dynamic Diffusion Transformer for Accurate Image Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, large compression leads to limited local realism, while small compression increases computational complexity and compromises global consistency, ultimately impacting the quality of generated images. To address these limitations, we propose dynamically compressing different image regions by recognizing the importance of different regions, and introduce a novel two-stage framework designed to enhance the effectiveness and efficiency of image generation: (1) Dynamic VAE (DVAE) at first stage employs a hierarchical encoder to encode different image regions at different downsampling rates, tailored to their specific information densities, thereby providing more accurate and natural latent codes for the diffusion process. |
Weinan Jia; Mengqi Huang; Nan Chen; Lei Zhang; Zhendong Mao; | cvpr | 2025-06-07 |
| 585 | BIS Reasoning 1.0: The First Large-Scale Japanese Benchmark for Belief-Inconsistent Syllogistic Reasoning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present BIS Reasoning 1.0, the first large-scale Japanese dataset ofsyllogistic reasoning problems explicitly designed to evaluatebelief-inconsistent reasoning in large language models (LLMs). |
HA-THANH NGUYEN et. al. | arxiv-cs.CL | 2025-06-07 |
| 586 | Self-Cross Diffusion Guidance for Text-to-Image Synthesis of Similar Subjects Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose Self-Cross Diffusion Guidance to penalize the overlap between cross-attention maps and the aggregated self-attention map. |
Weimin Qiu; Jieke Wang; Meng Tang; | cvpr | 2025-06-07 |
| 587 | AToM: Aligning Text-to-Motion Model at Event-Level with GPT-4Vision Reward Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, aligning motion generation with event-level textual descriptions presents unique challenges due to the complex, nuanced relationship between textual prompts and desired motion outcomes. To address this issue, we introduce AToM, a framework that enhances the alignment between generated motion and text prompts by leveraging reward from GPT-4Vision. |
HAONAN HAN et. al. | cvpr | 2025-06-07 |
| 588 | HSI-GPT: A General-Purpose Large Scene-Motion-Language Model for Human Scene Interaction Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose HSI-GPT, a General-Purpose Large Scene-Motion-Language Model that applies "next-token prediction" paradigm of Large Language Models to the HSI domain. |
Yuan Wang; Yali Li; Xiang Li; Shengjin Wang; | cvpr | 2025-06-07 |
| 589 | 3DTopia-XL: Scaling High-quality 3D Asset Generation Via Primitive Diffusion IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Despite recent advancements in 3D generative models, existing methods still face challenges with optimization speed, geometric fidelity, and the lack of assets for physically based rendering (PBR). In this paper, we introduce 3DTopia-XL, a scalable native 3D generative model designed to overcome these limitations. |
ZHAOXI CHEN et. al. | cvpr | 2025-06-07 |
| 590 | RLAIF-V: Open-Source AI Feedback Leads to Super GPT-4V Trustworthiness IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Traditional feedback learning for hallucination reduction relies on labor-intensive manual labeling or expensive proprietary models.This leaves the community without foundational knowledge about how to build high-quality feedback with open-source MLLMs.In this work, we introduce RLAIF-V, a novel framework that aligns MLLMs in a fully open-source paradigm. |
TIANYU YU et. al. | cvpr | 2025-06-07 |
| 591 | MAP: Unleashing Hybrid Mamba-Transformer Vision Backbone’s Potential with Masked Autoregressive Pretraining Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In contrast, pretraining strategies for hybrid architectures must be effective for both Mamba and Transformer components. Based on this, we propose Masked Autoregressive Pretraining (MAP) to pretrain a hybrid Mamba-Transformer vision backbone network. |
Yunze Liu; Li Yi; | cvpr | 2025-06-07 |
| 592 | LTG at SemEval-2025 Task 10: Optimizing Context for Classification of Narrative Roles Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Our contribution to the SemEval 2025 shared task 10, subtask 1 on entity framing, tackles the challenge of providing the necessary segments from longer documents as context for classification with a masked language model. |
Egil Rønningstad; Gaurav Negi; | arxiv-cs.CL | 2025-06-06 |
| 593 | A Structured Dataset for Automated Grading: From Raw Data to Processed Dataset Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The increasing volume of student assessments, particularly open-ended responses, presents a significant challenge for educators in ensuring grading accuracy, consistency, and … |
Ibidapo Dare Dada; A. Akinwale; Ti-Jesu Tunde-Adeleke; | Data | 2025-06-06 |
| 594 | The Lock-in Hypothesis: Stagnation By Algorithm Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The training and deployment of large language models (LLMs) create a feedback loop with human users: models learn human beliefs from data, reinforce these beliefs with generated content, reabsorb the reinforced beliefs, and feed them back to users again and again. |
Tianyi Alex Qiu; Zhonghao He; Tejasveer Chugh; Max Kleiman-Weiner; | arxiv-cs.LG | 2025-06-06 |
| 595 | MOGO: Residual Quantized Hierarchical Causal Transformer for High-Quality and Real-Time 3D Human Motion Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper,we propose MOGO (Motion Generation with One-pass), a novel autoregressiveframework tailored for efficient and real-time 3D motion generation. |
Dongjie Fu; Tengjiao Sun; Pengcheng Fang; Xiaohao Cai; Hansung Kim; | arxiv-cs.CV | 2025-06-06 |
| 596 | Can LLMs Talk ‘Sex’? Exploring How AI Models Handle Intimate Conversations Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study examines how four prominent large language models (Claude 3.7 Sonnet, GPT-4o, Gemini 2.5 Flash, and Deepseek-V3) handle sexually oriented requests through qualitative content analysis. |
Huiqian Lai; | arxiv-cs.CY | 2025-06-05 |
| 597 | On The Comprehensibility of Multi-structured Financial Documents Using LLMs and Pre-processing Tools Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper explores the capabilities of LLMs and MLLMs inunderstanding and answering questions from complex data structures found in PDFdocuments by leveraging industrial and open-source tools as part of apre-processing pipeline. |
Shivani Upadhyay; Messiah Ataey; Syed Shariyar Murtaza; Yifan Nie; Jimmy Lin; | arxiv-cs.IR | 2025-06-05 |
| 598 | F2T2-HiT: A U-Shaped FFT Transformer and Hierarchical Transformer for Reflection Removal Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: These reflections vary significantly in intensity, shapes, light sources, sizes, and coverage areas across the image, posing challenges for most existing methods to effectively handle all cases. To address these challenges, this paper introduces a U-shaped Fast Fourier Transform Transformer and Hierarchical Transformer (F2T2-HiT) architecture, an innovative Transformer-based design for SIRR. |
JIE CAI et. al. | arxiv-cs.CV | 2025-06-05 |
| 599 | Interpretable Multimodal Framework for Human-Centered Street Assessment: Integrating Visual-Language Models for Perceptual Urban Diagnostics Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study introduces a novel Multimodal Street Evaluation Framework (MSEF) that fuses a vision transformer (VisualGLM-6B) with a large language model (GPT-4), enabling interpretable dual-output assessment of streetscapes. |
HaoTian Lan; | arxiv-cs.CV | 2025-06-05 |
| 600 | Benchmarking Large Language Models on Homework Assessment in Circuit Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper investigates how LLMs can be leveraged in engineering education. |
Liangliang Chen; Zhihao Qin; Yiming Guo; Jacqueline Rohde; Ying Zhang; | arxiv-cs.CY | 2025-06-05 |
| 601 | Exploring Diffusion Transformer Designs Via Grafting Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View 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. | arxiv-cs.LG | 2025-06-05 |
| 602 | Reasoning or Overthinking: Evaluating Large Language Models on Financial Sentiment Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We investigate the effectiveness of large language models (LLMs), including reasoning-based and non-reasoning models, in performing zero-shot financial sentiment analysis. |
Dimitris Vamvourellis; Dhagash Mehta; | arxiv-cs.CL | 2025-06-04 |
| 603 | Exchange of Perspective Prompting Enhances Reasoning in Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, their performance is often limited by inherent comprehension of problems. To address this limitation, we propose Exchange-of-Perspective (EoP), a novel framework designed to exchange perspectives across different definitions of problem, so that it can break the fixed mindset from any particular formulation of the question. |
Lin Sun; Can Zhang; | arxiv-cs.CL | 2025-06-04 |
| 604 | A Threat Intelligence Event Extraction Conceptual Model for Cyber Threat Intelligence Feeds Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a systematic review of current techniques aimed at enhancing CTI data collection efficiency. |
Jamal H. Al-Yasiri; Mohamad Fadli Bin Zolkipli; Nik Fatinah N Mohd Farid; Mohammed Alsamman; Zainab Ali Mohammed; | arxiv-cs.CR | 2025-06-04 |
| 605 | TRIDENT — A Three-Tier Privacy-Preserving Propaganda Detection Model in Mobile Networks Using Transformers, Adversarial Learning, and Differential Privacy Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The proliferation of propaganda on mobile platforms raises critical concerns around detection accuracy and user privacy. To address this, we propose TRIDENT – a three-tier propaganda detection model implementing transformers, adversarial learning, and differential privacy which integrates syntactic obfuscation and label perturbation to mitigate privacy leakage while maintaining propaganda detection accuracy. |
Al Nahian Bin Emran; Dhiman Goswami; Md Hasan Ullah Sadi; Sanchari Das; | arxiv-cs.CR | 2025-06-04 |
| 606 | Facts Are Harder Than Opinions — A Multilingual, Comparative Analysis of LLM-Based Fact-Checking Reliability Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces a novel, dynamically extensibledata set that includes 61,514 claims in multiple languages and topics,extending existing datasets up to 2024. |
Lorraine Saju; Arnim Bleier; Jana Lasser; Claudia Wagner; | arxiv-cs.CY | 2025-06-04 |
| 607 | Facts Are Harder Than Opinions – A Multilingual, Comparative Analysis of LLM-Based Fact-Checking Reliability Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The proliferation of misinformation necessitates scalable, automated fact-checking solutions. Yet, current benchmarks often overlook multilingual and topical diversity. This paper … |
Lorraine Saju; Arnim Bleier; Jana Lasser; Claudia Wagner; | ArXiv | 2025-06-04 |
| 608 | Automatically Detecting Amusing Games in Wordle Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We explore automatically predicting which Wordle games Reddit users find amusing. |
RONALDO LUO et. al. | arxiv-cs.CL | 2025-06-04 |
| 609 | Enhancing Automatic PT Tagging for MEDLINE Citations Using Transformer-Based Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We investigated the feasibility of predicting Medical Subject Headings (MeSH) Publication Types (PTs) from MEDLINE citation metadata using pre-trained Transformer-based models BERT and DistilBERT. |
Victor H. Cid; James Mork; | arxiv-cs.DL | 2025-06-03 |
| 610 | Token and Span Classification for Entity Recognition in French Historical Encyclopedias Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose framing NER as both token-level and span-level classification to accommodate complex nested entity structures typical of historical documents. |
Ludovic Moncla; Hédi Zeghidi; | arxiv-cs.CL | 2025-06-03 |
| 611 | Rethinking The Effects of Data Contamination in Code Intelligence Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a systematic empirical study to investigate the fine-grained data contamination on code intelligence tasks. |
ZHEN YANG et. al. | arxiv-cs.SE | 2025-06-03 |
| 612 | Evaluating Named Entity Recognition Models for Russian Cultural News Texts: From BERT to LLM Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper addresses the challenge of Named Entity Recognition (NER) for person names within the specialized domain of Russian news texts concerning cultural events. |
Maria Levchenko; | arxiv-cs.CL | 2025-06-03 |
| 613 | Model Internal Sleuthing: Finding Lexical Identity and Inflectional Morphology in Modern Language Models Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Large transformer-based language models dominate modern NLP, yet our understanding of how they encode linguistic information is rooted in studies of early models like BERT and … |
Michael Li; Nishant Subramani; | ArXiv | 2025-06-02 |
| 614 | Unified Large Language Models for Misinformation Detection in Low-Resource Linguistic Settings Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents the first benchmark large FND dataset for Urdu news, which is publicly available for validation and deep analysis. |
Muhammad Islam; Javed Ali Khan; Mohammed Abaker; Ali Daud; Azeem Irshad; | arxiv-cs.CL | 2025-06-02 |
| 615 | Statement-Tuning Enables Efficient Cross-lingual Generalization in Encoder-only Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We extend this approach to multilingual NLP, exploring whether encoders can achieve zero-shot cross-lingual generalization and serve as efficient alternatives to memory-intensive LLMs for low-resource languages. |
AHMED ELSHABRAWY et. al. | arxiv-cs.CL | 2025-06-02 |
| 616 | Echoes of BERT: Do Modern Language Models Rediscover The Classical NLP Pipeline? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Building on classic BERTologywork, we analyze 25 models spanning from classical architectures (BERT,DeBERTa, GPT-2) to modern large language models (Pythia, OLMo-2, Gemma-2,Qwen2.5, Llama-3.1), probing layer-by-layer representations across eightlinguistic tasks in English. |
Michael Li; Nishant Subramani; | arxiv-cs.CL | 2025-06-02 |
| 617 | Speed-up of Vision Transformer Models By Attention-aware Token Filtering Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel speed-up method for ViT models called Attention-aware Token Filtering (ATF). |
Takahiro Naruko; Hiroaki Akutsu; | arxiv-cs.CV | 2025-06-02 |
| 618 | On Harnessing Semantic Communication With Natural Language Processing Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Through experimental endeavors, we explore the intersection of semantic communication (SemCom) and natural language processing (NLP) to address gaps in SemCom models, focusing on … |
Shiva Raj Pokhrel; Te’ Claire; | IEEE Internet of Things Journal | 2025-06-01 |
| 619 | How Do Transformer Embeddings Represent Compositions? A Functional Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: While transformer-based models have become the de facto standard for many language modeling tasks, little is known about how they represent compound words, and whether these representations are compositional. In this study, we test compositionality in Mistral, OpenAI Large, and Google embedding models, and compare them with BERT. |
Aishik Nagar; Ishaan Singh Rawal; Mansi Dhanania; Cheston Tan; | arxiv-cs.CL | 2025-06-01 |
| 620 | Is Random Attention Sufficient for Sequence Modeling? Disentangling Trainable Components in The Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: While the corecomponent of a transformer is the self-attention mechanism, we question howmuch, and which aspects, of the performance gains can be attributed to it. Tothis end, we compare standard transformers to variants in which either the MLPlayers or the attention weights are frozen at initialization. |
Yihe Dong; Lorenzo Noci; Mikhail Khodak; Mufan Li; | arxiv-cs.LG | 2025-06-01 |
| 621 | A Multi-Modal Assessment Framework for Comparison of Specialized Deep Learning and General-Purpose Large Language Models Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Recent years have witnessed tremendous advancements in Al tools (e.g., ChatGPT, GPT-4, and Bard), driven by the growing power, reasoning, and efficiency of Large Language Models … |
MOHAMMAD NADEEM et. al. | IEEE Transactions on Big Data | 2025-06-01 |
| 622 | Assisting Quality Assurance of Examination Tasks: Using A GPT Model and Bayesian Testing for Formative Assessment Related Papers Related Patents Related Grants Related Venues Related Experts View |
Nico Willert; Phi Katharina Würz; | Comput. Educ. Artif. Intell. | 2025-06-01 |
| 623 | This Is Human Intelligence Debugging Artificial Intelligence: Examining How People Prompt GPT in Seeking Mental Health Support Related Papers Related Patents Related Grants Related Venues Related Experts View |
Zhuoyang Li; Zihao Zhu; Xinning Gui; Yuhan Luo; | Int. J. Hum. Comput. Stud. | 2025-06-01 |
| 624 | TM2SP: A Transformer-Based Multi-Level Spatiotemporal Feature Pyramid Network for Video Saliency Prediction Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This paper proposes an end-to-end video saliency prediction network model, termed TM2SP-Net (Transformer-based Multi-level Spatiotemporal Feature Pyramid Network). Leveraging the … |
Chenming Li; Shiguang Liu; | IEEE Transactions on Circuits and Systems for Video … | 2025-06-01 |
| 625 | L3Cube-MahaEmotions: A Marathi Emotion Recognition Dataset with Synthetic Annotations Using CoTR Prompting and Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present L3Cube-MahaEmotions, ahigh-quality Marathi emotion recognition dataset with 11 fine-grained emotionlabels. |
Nidhi Kowtal; Raviraj Joshi; | arxiv-cs.CL | 2025-06-01 |
| 626 | MOFGPT: Generative Design of Metal–Organic Frameworks Using Language Models Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The discovery of Metal–Organic Frameworks (MOFs) with application-specific properties remains a central challenge in materials chemistry, owing to the immense size and complexity … |
Srivathsan Badrinarayanan; Rishikesh Magar; Akshay Antony; Radheesh Sharma Meda; A. Farimani; | Journal of Chemical Information and Modeling | 2025-05-30 |
| 627 | The World As Large Language Models See It: Exploring The Reliability of LLMs in Representing Geographical Features Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In the geocoding task, both models exhibited systematic and random errors in estimating the coordinates of St. Anne’s Column in Innsbruck, Austria, with GPT-4o showing greater deviations and Gemini 2.0 Flash demonstrating more precision but a significant systematic offset. For elevation estimation, both models tended to underestimate elevations across Austria, though they captured overall topographical trends, and Gemini 2.0 Flash performed better in eastern regions. |
Omid Reza Abbasi; Franz Welscher; Georg Weinberger; Johannes Scholz; | arxiv-cs.CY | 2025-05-30 |
| 628 | Evaluation of LLMs for Mathematical Problem Solving Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we compare three prominent LLMs,including GPT-4o, DeepSeek-V3, and Gemini-2.0, on three mathematics datasets ofvarying complexities (GSM8K, MATH500, and MIT Open Courseware datasets). |
RUONAN WANG et. al. | arxiv-cs.AI | 2025-05-30 |
| 629 | MELT: Towards Automated Multimodal Emotion Data Annotation By Leveraging LLM Embedded Knowledge Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: By crafting structured text prompts, our methodology capitalizes on the knowledge GPT-4o has accumulated during its training, showcasing that it can generate accurate and contextually relevant annotations without direct access to multimodal inputs. Therefore, we propose MELT, a multimodal emotion dataset fully annotated by GPT-4o. |
Xin Jing; Jiadong Wang; Iosif Tsangko; Andreas Triantafyllopoulos; Björn W. Schuller; | arxiv-cs.AI | 2025-05-30 |
| 630 | How Much Do Language Models Memorize? IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a new method for estimating how much a model knows about a datapoint and use it to measure the capacity of modern language models. |
JOHN X. MORRIS et. al. | arxiv-cs.CL | 2025-05-30 |
| 631 | MOFGPT: Generative Design of Metal-Organic Frameworks Using Language Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The complexity of MOFs, with their extended periodic structures and diverse topologies, creates both opportunities and challenges for generative modeling approaches. To address these challenges, we present a reinforcement learning-enhanced, transformer-based framework for the de novo design of MOFs. |
Srivathsan Badrinarayanan; Rishikesh Magar; Akshay Antony; Radheesh Sharma Meda; Amir Barati Farimani; | arxiv-cs.LG | 2025-05-30 |
| 632 | An Evaluation of LLMs for Generating Movie Reviews: GPT-4o, Gemini-2.0 and DeepSeek-V3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we propose a framework that generates movie reviews using three LLMs (GPT-4o, DeepSeek-V3, and Gemini-2.0), and evaluate their performance by comparing the generated outputs with IMDb user reviews. |
BRENDAN SANDS et. al. | arxiv-cs.CL | 2025-05-30 |
| 633 | Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, as the most straightforward characteristic of code, we investigate the relationship between code complexity and the success of LLM generated code. |
Melika Sepidband; Hamed Taherkhani; Song Wang; Hadi Hemmati; | arxiv-cs.SE | 2025-05-29 |
| 634 | Evaluating AI Capabilities in Detecting Conspiracy Theories on YouTube Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This study explores the use ofopen-weight Large Language Models (LLMs), both text-only and multimodal, foridentifying conspiracy theory videos shared on YouTube. |
Leonardo La Rocca; Francesco Corso; Francesco Pierri; | arxiv-cs.CL | 2025-05-29 |
| 635 | Hidden Persuasion: Detecting Manipulative Narratives on Social Media During The 2022 Russian Invasion of Ukraine Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents one of the top-performing solutions to the UNLP 2025 Shared Task on Detecting Manipulation in Social Media. |
Kateryna Akhynko; Oleksandr Kosovan; Mykola Trokhymovych; | arxiv-cs.CL | 2025-05-29 |
| 636 | AI-Mediated Dispute Resolution Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: We examine the effectiveness of large language model (LLM) mediations in the under-studied dispute resolution domain. We first used a new corpus of dispute resolutions, KODIS, to … |
James Hale; Hanmoe Kim; Ahyoung Choi; Jonathan Gratch; | AAAI Spring Symposia | 2025-05-28 |
| 637 | Legal Assist AI: Leveraging Transformer-Based Model for Effective Legal Assistance Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Pursuit of accessible legal assistance in India faces a critical gap, as many citizens struggle to leverage their legal rights due to limited awareness and access to relevant legal information. This paper introduces Legal Assist AI, a transformer-based model designed to bridge this gap by offering effective legal assistance through large language models (LLMs). |
Jatin Gupta; Akhil Sharma; Saransh Singhania; Ali Imam Abidi; | arxiv-cs.CL | 2025-05-28 |
| 638 | Improving QA Efficiency with DistilBERT: Fine-Tuning and Inference on Mobile Intel CPUs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study presents an efficient transformer-based question-answering (QA) model optimized for deployment on a 13th Gen Intel i7-1355U CPU, using the Stanford Question Answering Dataset (SQuAD) v1.1. |
Ngeyen Yinkfu; | arxiv-cs.CL | 2025-05-28 |
| 639 | Learning in Compact Spaces with Approximately Normalized Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a more holistic but approximate normalization (anTransformer). |
JÖRG K. H. FRANKE et. al. | arxiv-cs.LG | 2025-05-28 |
| 640 | Leveraging Large Language Models and Traditional Machine Learning Ensembles for ADHD Detection from Narrative Transcripts Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we introduce an ensemble framework for automatically classifying Attention-Deficit/Hyperactivity Disorder (ADHD) diagnosis (binary) using narrative transcripts. |
Yuxin Zhu; Yuting Guo; Noah Marchuck; Abeed Sarker; Yun Wang; | arxiv-cs.CL | 2025-05-27 |
| 641 | Taming Transformer Without Using Learning Rate Warmup Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we provide a theoretical analysis for the process of training Transformer and reveal the rationale behind the model crash phenomenon in the training process, termed \textit{spectral energy concentration} of ${\bW_q}^{\top} \bW_k$, which is the reason for a malignant entropy collapse, where ${\bW_q}$ and $\bW_k$ are the projection matrices for the query and the key in Transformer, respectively. |
XIANBIAO QI et. al. | arxiv-cs.LG | 2025-05-27 |
| 642 | Self-supervised Learning Method Using Transformer for Multi-dimensional Sensor Data Processing Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we built a pretrained language model based on the Transformer architecture, which is widely used in natural language processing. |
Haruki Kai; Tsuyoshi Okita; | arxiv-cs.LG | 2025-05-27 |
| 643 | Explaining Large Language Models with GSMILE Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present gSMILE (generative SMILE), a model-agnostic,perturbation-based framework for token-level interpretability in LLMs.Extending the SMILE methodology, gSMILE uses controlled prompt perturbations,Wasserstein distance metrics, and weighted linear surrogates to identify inputtokens with the most significant impact on the output. |
Zeinab Dehghani; Mohammed Naveed Akram; Koorosh Aslansefat; Adil Khan; Yiannis Papadopoulos; | arxiv-cs.CL | 2025-05-27 |
| 644 | Transformers in Protein: A Survey Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This review aims to provide a consolidated foundation for the synergistic integration of Transformer and protein informatics, fostering further innovation and expanded applications in the field. |
Xiaowen Ling; Zhiqiang Li; Yanbin Wang; Zhuhong You; | arxiv-cs.LG | 2025-05-26 |
| 645 | Detection of Suicidal Risk on Social Media: A Hybrid Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Suicidal thoughts and behaviors are increasingly recognized as a critical societal concern, highlighting the urgent need for effective tools to enable early detection of suicidal risk. In this work, we develop robust machine learning models that leverage Reddit posts to automatically classify them into four distinct levels of suicide risk severity. |
Zaihan Yang; Ryan Leonard; Hien Tran; Rory Driscoll; Chadbourne Davis; | arxiv-cs.CL | 2025-05-26 |
| 646 | Beyond Specialization: Benchmarking LLMs for Transliteration of Indian Languages Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Transliteration, the process of mapping text from one script to another, plays a crucial role in multilingual natural language processing, especially within linguistically diverse … |
GULFAROGH AZAM et. al. | arxiv-cs.CL | 2025-05-26 |
| 647 | Understanding Transformer from The Perspective of Associative Memory Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we share our reflections and insights on understanding Transformer architectures through the lens of associative memory–a classic psychological concept inspired by human cognition. |
Shu Zhong; Mingyu Xu; Tenglong Ao; Guang Shi; | arxiv-cs.LG | 2025-05-26 |
| 648 | Automated Evaluation of Children’s Speech Fluency for Low-resource Languages Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes a system to automatically assess fluency by combining a fine-tuned multilingual ASR model, an objective metrics extraction stage, and a generative pre-trained transformer (GPT) network. |
BOWEN ZHANG et. al. | arxiv-cs.SD | 2025-05-26 |
| 649 | Benchmarking Large Multimodal Models for Ophthalmic Visual Question Answering with OphthalWeChat Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Subset-specific performance showed Gemini 2.0 Flash excelled in Binary_CN (0.687), Single-choice_CN (0.666), and Single-choice_EN (0.646), while GPT-4o ranked highest in Binary_EN (0.717), Open-ended_CN (BLEU-1: 0.301; BERTScore: 0.382), and Open-ended_EN (BLEU-1: 0.183; BERTScore: 0.240). Conclusions: This study presents the first bilingual VQA benchmark for ophthalmology, distinguished by its real-world context and inclusion of multiple examinations per patient. |
PUSHENG XU et. al. | arxiv-cs.CV | 2025-05-26 |
| 650 | Conversational Lexicography: Querying Lexicographic Data on Knowledge Graphs with SPARQL Through Natural Language Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper addresses the challenge of creating natural language interfaces for lexicographic data retrieval on knowledge graphs such as Wikidata. |
Kilian Sennrich; Sina Ahmadi; | arxiv-cs.CL | 2025-05-26 |
| 651 | NextG-GPT: Leveraging GenAI for Advancing Wireless Networks and Communication Research Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce Next-Generation GPT (NextG-GPT), an innovative framework that integrates retrieval-augmented generation (RAG) and large language models (LLMs) within the wireless systems’ domain. |
Ahmad M. Nazar; Mohamed Y. Selim; Daji Qiao; Hongwei Zhang; | arxiv-cs.ET | 2025-05-25 |
| 652 | AI4Math: A Native Spanish Benchmark for University-Level Mathematical Reasoning in Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Existing mathematical reasoning benchmarks are predominantly English only or translation-based, which can introduce semantic drift and mask languagespecific reasoning errors. To address this, we present AI4Math, a benchmark of 105 original university level math problems natively authored in Spanish. |
MIGUEL ANGEL PEÑALOZA PEREZ et. al. | arxiv-cs.CL | 2025-05-25 |
| 653 | Optimized Text Embedding Models and Benchmarks for Amharic Passage Retrieval Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, their effectiveness for low-resource, morphologically rich languages such as Amharic remains underexplored due to data scarcity and suboptimal tokenization. We address this gap by introducing Amharic-specific dense retrieval models based on pre-trained Amharic BERT and RoBERTa backbones. |
Kidist Amde Mekonnen; Yosef Worku Alemneh; Maarten de Rijke; | arxiv-cs.IR | 2025-05-25 |
| 654 | Evaluating AI for Finance: Is AI Credible at Assessing Investment Risk? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We assess whether AI systems can credibly evaluate investment risk appetite-atask that must be thoroughly validated before automation. |
DIVIJ CHAWLA et. al. | arxiv-cs.CL | 2025-05-24 |
| 655 | Multi-Scale Manifold Alignment for Interpreting Large Language Models: A Unified Information-Geometric Framework Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present Multi-Scale Manifold Alignment(MSMA), an information-geometricframework that decomposes LLM representations into local, intermediate, andglobal manifolds and learns cross-scale mappings that preserve geometry andinformation. |
Yukun Zhang; Qi Dong; | arxiv-cs.CL | 2025-05-24 |
| 656 | Is It Bad to Work All The Time? Cross-Cultural Evaluation of Social Norm Biases in GPT-4 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To address that, we take a bottom-up approach, asking LLMs to reason about cultural norms in narratives from different cultures. |
Zhuozhuo Joy Liu; Farhan Samir; Mehar Bhatia; Laura K. Nelson; Vered Shwartz; | arxiv-cs.CL | 2025-05-23 |
| 657 | OmniConsistency: Learning Style-Agnostic Consistency from Paired Stylization Data Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View 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; | arxiv-cs.CV | 2025-05-23 |
| 658 | AI-Augmented LLMs Achieve Therapist-Level Responses in Motivational Interviewing Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present a computational framework assessing user-perceived quality (UPQ) through expected and unexpected MI behaviors. |
YINGHUI HUANG et. al. | arxiv-cs.CL | 2025-05-22 |
| 659 | Understanding Differential Transformer Unchains Pretrained Self-Attentions Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Moreover,Differential Transformer architecture demands large-scale training fromscratch, hindering utilization of open pretrained weights. In this work, weconduct an in-depth investigation of Differential Transformer, uncovering threekey factors behind its success: (1) enhanced expressivity via negativeattention, (2) reduced redundancy among attention heads, and (3) improvedlearning dynamics. |
Chaerin Kong; Jiho Jang; Nojun Kwak; | arxiv-cs.LG | 2025-05-22 |
| 660 | Fusion of Foundation and Vision Transformer Model Features for Dermatoscopic Image Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we investigate the utility of a dermatology-specific foundation model, PanDerm, in comparison with two Vision Transformer (ViT) architectures (ViT base and Swin Transformer V2 base) for the task of skin lesion classification. |
Amirreza Mahbod; Rupert Ecker; Ramona Woitek; | arxiv-cs.CV | 2025-05-22 |
| 661 | Can ChatGPT Perform Image Splicing Detection? A Preliminary Study Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: Multimodal Large Language Models (MLLMs) like GPT-4V are capable of reasoning across text and image modalities, showing promise in a variety of complex vision-language tasks. In … |
Souradip Nath; | ArXiv | 2025-05-22 |
| 662 | Foundation Models for Geospatial Reasoning: Assessing Capabilities of Large Language Models in Understanding Geometries and Topological Spatial Relations Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Applying AI foundation models directly to geospatial datasets remains challenging due to their limited ability to represent and reason with geographical entities, specifically vector-based geometries and natural language descriptions of complex spatial relations. |
Yuhan Ji; Song Gao; Ying Nie; Ivan Majić; Krzysztof Janowicz; | arxiv-cs.CL | 2025-05-22 |
| 663 | LINEA: Fast and Accurate Line Detection Using Scalable Transformers Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper develops a new transformer-based method that is significantly faster without requiring pretraining the attention mechanism on large datasets. |
Sebastian Janampa; Marios Pattichis; | arxiv-cs.CV | 2025-05-22 |
| 664 | GPT Editors, Not Authors: The Stylistic Footprint of LLMs in Academic Preprints Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We seek to determine the degree to which LLMs are used to generate critical text as opposed to being used for editing, such as checking for grammar errors or inappropriate phrasing. |
Soren DeHaan; Yuanze Liu; Johan Bollen; Sa’ul A. Blanco; | arxiv-cs.CL | 2025-05-22 |
| 665 | Data-Driven Breakthroughs and Future Directions in AI Infrastructure: A Comprehensive Review Related Papers Related Patents Related Grants Related Venues Related Experts View 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. |
Beyazit Bestami Yuksel; Ayse Yilmazer Metin; | arxiv-cs.AI | 2025-05-22 |
| 666 | Web-Shepherd: Advancing PRMs for Reinforcing Web Agents Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View 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. | arxiv-cs.CL | 2025-05-21 |
| 667 | Multilingual Prompting for Improving LLM Generation Diversity Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Through experiments across multiple models (GPT-4o, GPT-4o-mini, LLaMA70B, and LLaMA 8B), we show that multilingual prompting consistentlyoutperforms existing diversity-enhancing techniques such as high-temperaturesampling, step-by-step recall, and persona prompting. |
Qihan Wang; Shidong Pan; Tal Linzen; Emily Black; | arxiv-cs.CL | 2025-05-21 |
| 668 | Polarity of Yelp Reviews: A BERT-LSTM Comparative Study Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: With the rapid growth in social network comments, the need for more effective methods to classify their polarity—negative, neutral, or positive—has become essential. Sentiment … |
R. Belaroussi; Sié Cyriac Noufe; F. Dupin; P. Vandanjon; | Big Data Cogn. Comput. | 2025-05-21 |
| 669 | AdUE: Improving Uncertainty Estimation Head for LoRA Adapters in LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce AdUE1, an efficient post-hoc uncertainty estimation (UE) method, to enhance softmax-based estimates. |
ARTEM ZABOLOTNYI et. al. | arxiv-cs.CL | 2025-05-21 |
| 670 | RLBenchNet: The Right Network for The Right Reinforcement Learning Task Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this study, we systematically investigate the performance of several neural networks in RL tasks, including Long Short-Term Memory (LSTM), Multi-Layer Perceptron (MLP), Mamba/Mamba-2, Transformer-XL, Gated Transformer-XL, and Gated Recurrent Unit (GRU). |
Ivan Smirnov; Shangding Gu; | arxiv-cs.LG | 2025-05-20 |
| 671 | Interpretable Dual-Stream Learning for Local Wind Hazard Prediction in Vulnerable Communities Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Existing forecasting systems focus primarily on meteorological elements and often fail to capture community-specific vulnerabilities, limiting their utility for localized risk assessment and resilience planning. To address this gap, we propose an interpretable dual-stream learning framework that integrates structured numerical weather data with unstructured textual event narratives. |
Mahmuda Akhter Nishu; Chenyu Huang; Milad Roohi; Xin Zhong; | arxiv-cs.LG | 2025-05-20 |
| 672 | Scaling Laws for State Dynamics in Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Large Language Models (LLMs) are increasingly used in tasks requiring internal state tracking, yet their ability to model state transition dynamics remains poorly understood. |
Jacob X Li; Shreyas S Raman; Jessica Wan; Fahad Samman; Jazlyn Lin; | arxiv-cs.CL | 2025-05-20 |
| 673 | Choosing A Model, Shaping A Future: Comparing LLM Perspectives on Sustainability and Its Relationship with AI Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: As organizations increasingly rely on AI systems for decision support insustainability contexts, it becomes critical to understand the inherent biasesand perspectives embedded in … |
Annika Bush; Meltem Aksoy; Markus Pauly; Greta Ontrup; | arxiv-cs.CY | 2025-05-20 |
| 674 | Tokenization Constraints in LLMs: A Study of Symbolic and Arithmetic Reasoning Limits Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work presents a theoretical and empirical investigation into how tokenization schemes, particularly subword-based methods like byte-pair encoding (BPE), impede symbolic computation by merging or obscuring atomic reasoning units. |
Xiang Zhang; Juntai Cao; Jiaqi Wei; Yiwei Xu; Chenyu You; | arxiv-cs.CL | 2025-05-20 |
| 675 | Probing BERT for German Compound Semantics Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper investigates the extent to which pretrained German BERT encodes knowledge of noun compound semantics. |
Filip Miletić; Aaron Schmid; Sabine Schulte im Walde; | arxiv-cs.CL | 2025-05-20 |
| 676 | EEG-to-Text Translation: A Model for Deciphering Human Brain Activity Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, these models still face significant performance limitations. To overcome these shortcomings, we propose a new model, R1 Translator, which aims to improve the performance of EEG-to-text decoding. |
Saydul Akbar Murad; Ashim Dahal; Nick Rahimi; | arxiv-cs.CL | 2025-05-20 |
| 677 | Cost-Augmented Monte Carlo Tree Search for LLM-Assisted Planning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce Cost-Augmented Monte Carlo Tree Search (CATS), a novel approach that brings explicit cost-awareness into LLM-guided planning. |
Zihao Zhang; Fei Liu; | arxiv-cs.AI | 2025-05-20 |
| 678 | The Hidden Structure — Improving Legal Document Understanding Through Explicit Text Formatting Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper investigates the effects of explicit input text structure and prompt engineering on the performance of GPT-4o and GPT-4.1 on a legal question-answering task using an excerpt of the CUAD. |
Christian Braun; Alexander Lilienbeck; Daniel Mentjukov; | arxiv-cs.CL | 2025-05-19 |
| 679 | To Bias or Not to Bias: Detecting Bias in News with Bias-detector Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we perform sentence-level bias classification by fine-tuning a RoBERTa-based model on the expert-annotated BABE dataset. |
Himel Ghosh; Ahmed Mosharafa; Georg Groh; | arxiv-cs.CL | 2025-05-19 |
| 680 | OMGPT: A Sequence Modeling Framework for Data-driven Operational Decision Making Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We build a Generative Pre-trained Transformer (GPT) model from scratch to solve sequential decision making tasks arising in contexts of operations research and management science which we call OMGPT. |
Hanzhao Wang; Guanting Chen; Kalyan Talluri; Xiaocheng Li; | arxiv-cs.LG | 2025-05-19 |
| 681 | PiT: Progressive Diffusion Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Based on theseinnovations, we propose a series of Pseudo Progressive Diffusion Transformer(PiT). |
JIAFU WU et. al. | arxiv-cs.CV | 2025-05-19 |
| 682 | MSVIT: Improving Spiking Vision Transformer Using Multi-scale Attention Fusion Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: While existing methods propose spiking self-attention mechanisms that are successfully combined with SNNs, the overall architectures proposed by these methods suffer from a bottleneck in effectively extracting features from different image scales. In this paper, we address this issue and propose MSVIT. |
Wei Hua; Chenlin Zhou; Jibin Wu; Yansong Chua; Yangyang Shu; | arxiv-cs.CV | 2025-05-19 |
| 683 | CausalFormer: An Interpretable Transformer for Temporal Causal Discovery (Extended Abstract) Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Current deep learning-based methods usually analyze the parameters of some components of the trained models, which is an incomplete mapping process from the model parameters to the causality and fails to investigate the other components. To address this, this paper presents an interpretable transformer-based causal discovery model termed CausalFormer, which consists of: 1) the causality-aware transformer which learns the causal representation with the multi-kernel causal convolution under the temporal priority constraint, and 2) the decomposition-based causality detector which identifies causality by interpreting the global structure of the trained transformer with the regression relevance propagation. |
LINGBAI KONG et. al. | icde | 2025-05-19 |
| 684 | The Traitors: Deception and Trust in Multi-Agent Language Model Simulations Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce The Traitors, a multi-agent simulation framework inspired by social deduction games, designed to probe deception, trust formation, and strategic communication among large language model (LLM) agents under asymmetric information. |
Pedro M. P. Curvo; | arxiv-cs.AI | 2025-05-19 |
| 685 | Assessing GPT Performance in A Proof-Based University-Level Course Under Blind Grading Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study assesses the performance of GPT-4o and o1-preview under realistic educational conditions in an undergraduate algorithms course. |
Ming Ding; Rasmus Kyng; Federico Solda; Weixuan Yuan; | arxiv-cs.CY | 2025-05-19 |
| 686 | Are Large Language Models Good at Detecting Propaganda? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we look at several Large Language Models and their performance in detecting propaganda techniques in news articles. |
Julia Jose; Rachel Greenstadt; | arxiv-cs.CL | 2025-05-19 |
| 687 | Video-GPT Via Next Clip Diffusion Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Alternatively, the video sequence is good at capturing such details. Motivated by this fact, we propose a concise Video-GPT in this paper by treating video as new language for visual world modeling. |
SHAOBIN ZHUANG et. al. | arxiv-cs.CV | 2025-05-18 |
| 688 | KGAlign: Joint Semantic-Structural Knowledge Encoding for Multimodal Fake News Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To address thesechallenges, we propose a novel multi-modal fake news detection framework thatintegrates visual, textual, and knowledge-based representations. |
Tuan-Vinh La; Minh-Hieu Nguyen; Minh-Son Dao; | arxiv-cs.CV | 2025-05-18 |
| 689 | Let The Trial Begin: A Mock-Court Approach to Vulnerability Detection Using LLM-Based Agents Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we introduce VulTrial, a courtroom-inspired multi-agent framework designed to enhance automated vulnerability detection. |
RATNADIRA WIDYASARI et. al. | arxiv-cs.SE | 2025-05-16 |
| 690 | Transforming Decoder-Only Transformers for Accurate WiFi-Telemetry Based Indoor Localization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Currently, there is no unified model to handle all these variations effectively. In this paper, we present WiFiGPT, a Generative Pretrained Transformer (GPT) based system that is able to handle these variations while achieving high localization accuracy. |
Nayan Sanjay Bhatia; Katia Obraczka; | arxiv-cs.NI | 2025-05-16 |
| 691 | ACSE-Eval: Can LLMs Threat Model Real-world Cloud Infrastructure? Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper introduces AWS Cloud Security Engineering Eval, a novel dataset for evaluating LLMs cloud security threat modeling capabilities. |
SARTHAK MUNSHI et. al. | arxiv-cs.CR | 2025-05-16 |
| 692 | Code-Driven Planning in Grid Worlds with Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose an iterative programmatic planning (IPP) framework for solving grid-based tasks by synthesizing interpretable agent policies expressed in code using large language models (LLMs). |
Ashwath Vaithinathan Aravindan; Zhisheng Tang; Mayank Kejriwal; | arxiv-cs.AI | 2025-05-15 |
| 693 | Integrated Digital Twins System for Oil Temperature Prediction of Power Transformer Based on Internet of Things Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Oil temperature is an important index to reflect the state of transformer and predict the fault and remaining useful life of transformer. However, the oil temperature of the … |
Zhihan Lyu; Zhibo Wan; Zengxu Bian; Yuqi Liu; Wei Zhao; | IEEE Internet of Things Journal | 2025-05-15 |
| 694 | Optimal Control for Transformer Architectures: Enhancing Generalization, Robustness and Efficiency Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We conduct seven extensive experiments on tasks motivated by text generation, sentiment analysis, image classification, and point cloud classification. |
KELVIN KAN et. al. | arxiv-cs.LG | 2025-05-15 |
| 695 | Sentiment-driven Cryptocurrency Forecasting: Analyzing LSTM, GRU, Bi-LSTM, and Temporal Attention Model (TAM) Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Predicting cryptocurrency prices is challenging due to market volatility and external influences like social media sentiment. This study integrates Twitter sentiment analysis with … |
Phumudzo Lloyd Seabe; C. Moutsinga; Edson Pindza; | Soc. Netw. Anal. Min. | 2025-05-14 |
| 696 | Zero-Shot Multi-modal Large Language Model V.s. Supervised Deep Learning: A Comparative Study on CT-Based Intracranial Hemorrhage Subtyping Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Methods: We utilized a dataset provided by RSNA, comprising 192 NCCT volumes. |
YINUO WANG et. al. | arxiv-cs.CV | 2025-05-14 |
| 697 | Small But Significant: On The Promise of Small Language Models for Accessible AIED Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: A simple keyword-based search reveals that 61% of the 76 long and short papers presented at AIED 2024 describe novel solutions using LLMs to address some of the long-standing challenges in education, and 43% specifically mention GPT. |
Yumou Wei; Paulo Carvalho; John Stamper; | arxiv-cs.CL | 2025-05-13 |
| 698 | For GPT-4 As with Humans: Information Structure Predicts Acceptability of Long-Distance Dependencies Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Study 2 manipulates the information structure of base sentences and confirms a causal relationship: increasing the prominence of a constituent in a context sentence increases the subsequent acceptability ratings on an LDD construction. |
Nicole Cuneo; Eleanor Graves; Supantho Rakshit; Adele E. Goldberg; | arxiv-cs.CL | 2025-05-13 |
| 699 | A Suite of LMs Comprehend Puzzle Statements As Well As Humans Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Here, we revisit those findings and argue that human performance was overestimated, while LLM abilities were underestimated. |
Adele E Goldberg; Supantho Rakshit; Jennifer Hu; Kyle Mahowald; | arxiv-cs.CL | 2025-05-13 |
| 700 | LLM-based Prompt Ensemble for Reliable Medical Entity Recognition from EHRs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper explores prompt-based medical entity recognition using large language models (LLMs), specifically GPT-4o and DeepSeek-R1, guided by various prompt engineering techniques, including zero-shot, few-shot, and an ensemble approach. |
K M Sajjadul Islam; Ayesha Siddika Nipu; Jiawei Wu; Praveen Madiraju; | arxiv-cs.AI | 2025-05-13 |
| 701 | HealthBench: Evaluating Large Language Models Towards Improved Human Health IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present HealthBench, an open-source benchmark measuring the performance and safety of large language models in healthcare. |
RAHUL K. ARORA et. al. | arxiv-cs.CL | 2025-05-13 |
| 702 | AI-Mediated Code Comment Improvement Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper describes an approach to improve code comments along different quality axes by rewriting those comments with customized Artificial Intelligence (AI)-based tools. |
MARIA DHAKAL et. al. | arxiv-cs.SE | 2025-05-13 |
| 703 | GPTracker: A Large-Scale Measurement of Misused GPTs Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Large language model (LLM)-powered agents, particularly GPTs by OpenAI, have revolutionized how AI is customized, deployed, and used. However, misuse of GPTs has emerged as a … |
Xinyue Shen; Yun Shen; Michael Backes; Yang Zhang; | 2025 IEEE Symposium on Security and Privacy (SP) | 2025-05-12 |
| 704 | GRADA: Graph-based Reranking Against Adversarial Documents Attack Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Thus, we propose a simple yet effective Graph-basedReranking against Adversarial Document Attacks (GRADA) framework aiming atpreserving retrieval quality while significantly reducing the success ofadversaries. |
JINGJIE ZHENG et. al. | arxiv-cs.IR | 2025-05-12 |
| 705 | A Large-Scale Empirical Analysis of Custom GPTs’ Vulnerabilities in The OpenAI Ecosystem Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this study, we analyze 14,904 custom GPTs to assess their susceptibility to seven exploitable threats, such as roleplay-based attacks, system prompt leakage, phishing content generation, and malicious code synthesis, across various categories and popularity tiers within the OpenAI marketplace. |
Sunday Oyinlola Ogundoyin; Muhammad Ikram; Hassan Jameel Asghar; Benjamin Zi Hao Zhao; Dali Kaafar; | arxiv-cs.CR | 2025-05-12 |
| 706 | Lost in Transmission: When and Why LLMs Fail to Reason Globally Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Despite their many successes, transformer-based large language models (LLMs)continue to struggle with tasks that require complex reasoning over large partsof their input. We argue that these failures arise due to capacity limits onthe accurate flow of information within LLMs. |
Tobias Schnabel; Kiran Tomlinson; Adith Swaminathan; Jennifer Neville; | arxiv-cs.AI | 2025-05-12 |
| 707 | Comparative Sentiment Analysis of Public Perception: Monkeypox Vs. COVID-19 Behavioral Insights Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study conducts a comparative sentimentanalysis of public perceptions surrounding COVID-19 and mpox by leveragingextensive datasets of 147,475 and 106,638 tweets, respectively. |
Mostafa Mohaimen Akand Faisal; Rabeya Amin Jhuma; Jamini Jasim; | arxiv-cs.CL | 2025-05-12 |
| 708 | Attention Is Not All You Need: The Importance of Feedforward Networks in Transformer Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we examine the importance of the FFN during the model pre-training process through a series of experiments, confirming that the FFN is important to model performance. |
Isaac Gerber; | arxiv-cs.CL | 2025-05-10 |
| 709 | An Empathic GPT-based Chatbot to Talk About Mental Disorders with Spanish Teenagers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a chatbot-based system to engage young Spanish people in the awareness of certain mental disorders through a self-disclosure technique. |
Alba María Mármol-Romero; Manuel García-Vega; Miguel Ángel García-Cumbreras; Arturo Montejo-Ráez; | arxiv-cs.HC | 2025-05-09 |
| 710 | Towards Robust Few-Shot Text Classification Using Transformer Architectures and Dual Loss Strategies Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes a strategy that combines adaptive fine-tuning, contrastive learning, and regularization optimization to improve the classification performance of Transformer-based models. |
Xu Han; Yumeng Sun; Weiqiang Huang; Hongye Zheng; Junliang Du; | arxiv-cs.CL | 2025-05-09 |
| 711 | Multimodal Sentiment Analysis on CMU-MOSEI Dataset Using Transformer-based Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This project performs multimodal sentiment analysis using the CMU-MOSEIdataset, using transformer-based models with early fusion to integrate text,audio, and visual modalities. |
Jugal Gajjar; Kaustik Ranaware; | arxiv-cs.CL | 2025-05-09 |
| 712 | Cardioformer: Advancing AI in ECG Analysis with Multi-Granularity Patching and ResNet Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Electrocardiogram (ECG) classification is crucial for automated cardiac disease diagnosis, yet existing methods often struggle to capture local morphological details and long-range temporal dependencies simultaneously. To address these challenges, we propose Cardioformer, a novel multi-granularity hybrid model that integrates cross-channel patching, hierarchical residual learning, and a two-stage self-attention mechanism. |
Md Kamrujjaman Mobin; Md Saiful Islam; Sadik Al Barid; Md Masum; | arxiv-cs.LG | 2025-05-08 |
| 713 | A Preliminary Study for GPT-4o on Image Restoration Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: OpenAI’s GPT-4o model, integrating multi-modal inputs and outputs within an autoregressive architecture, has demonstrated unprecedented performance in image generation. In this work, we investigate its potential impact on the image restoration community. |
Hao Yang; Yan Yang; Ruikun Zhang; Liyuan Pan; | arxiv-cs.CV | 2025-05-08 |
| 714 | AI Approaches to Qualitative and Quantitative News Analytics on NATO Unity Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This approach does not aim to conduct real political analysis; rather, it consider AI based approaches which can be used for further analytics as a part of a complex analytical approach. |
Bohdan M. Pavlyshenko; | arxiv-cs.IR | 2025-05-08 |
| 715 | Empirical Evaluation of Prompting Strategies for Fact Verification Tasks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Commercial large language models (LLMs) such as GPT-3.5 have emerged as powerful tools for diverse natural language processing (NLP) tasks, yet concerns persist about their … |
Mohna Chakraborty; Adithya Kulkarni; Qi Li; | Companion Proceedings of the ACM on Web Conference 2025 | 2025-05-08 |
| 716 | REVEAL: Multi-turn Evaluation of Image-Input Harms for Vision LLM Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Traditional safety evaluation frameworks, designed for text-based, single-turn interactions, are inadequate for addressing these complexities. To bridge this gap, we introduce the REVEAL (Responsible Evaluation of Vision-Enabled AI LLMs) Framework, a scalable and automated pipeline for evaluating image-input harms in VLLMs. |
Madhur Jindal; Saurabh Deshpande; | arxiv-cs.CL | 2025-05-07 |
| 717 | Preliminary Explorations with GPT-4o(mni) Native Image Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we aim to explore the capabilities of GPT-4o across various tasks. |
PU CAO et. al. | arxiv-cs.CV | 2025-05-06 |
| 718 | Efficient Vision Transformer: Application of Data-efficient Image Transformer for Aero Engine Bearing Fault Classification Related Papers Related Patents Related Grants Related Venues Related Experts View |
Xin Deng; Xubing Fang; Gangjin Huang; Junheng Fu; | Signal Image Video Process. | 2025-05-06 |
| 719 | Improving Sentiment Analysis in Literary Texts Through Bidirectional Encoder Representations: A BERT-based Approach Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Emotion analysis in literary texts is a complex task due to the intricate nature of language, rich contextual dependencies, and subtle emotional manifestations present in … |
Jiawen Feng; | J. Comput. Methods Sci. Eng. | 2025-05-05 |
| 720 | GAME: Learning Multimodal Interactions Via Graph Structures for Personality Trait Estimation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose GAME, a Graph-Augmented Multimodal Encoder designed to robustly model and fuse multi-source features for automatic personality prediction. |
KANGSHENG WANG et. al. | arxiv-cs.CV | 2025-05-05 |
| 721 | Logits-Constrained Framework with RoBERTa for Ancient Chinese NER Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a Logits-Constrained (LC) framework for Ancient Chinese Named Entity Recognition (NER), evaluated on the EvaHan 2025 benchmark. |
Wenjie Hua; Shenghan Xu; | arxiv-cs.CL | 2025-05-05 |
| 722 | Learning to Substitute Words with Model-based Score Ranking Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To circumvent this issue, we instead employ a model-based scoring (BARTScore) to quantify sentence quality, thus forgoing the need for human annotations. Specifically, we use this score to define a distribution for each word substitution, allowing one to test whether a substitution is statistically superior relative to others. |
Hongye Liu; Ricardo Henao; | naacl | 2025-05-04 |
| 723 | TurboFuzzLLM: Turbocharging Mutation-based Fuzzing for Effectively Jailbreaking Large Language Models in Practice Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present TurboFuzzLLM, a mutation-based fuzzing technique for efficiently finding a collection of effective jailbreaking templates that, when combined with harmful questions, can lead a target LLM to produce harmful responses through black-box access via user prompts. |
Aman Goel; Xian Wu; Zhe Wang; Dmitriy Bespalov; Yanjun Qi; | naacl | 2025-05-04 |
| 724 | PlagBench: Exploring The Duality of Large Language Models in Plagiarism Generation and Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Also, how LLMs can facilitate the detection of LLM-generated plagiarism remains largely unexplored. To address these gaps, we introduce PlagBench, a dataset of 46. |
JOOYOUNG LEE et. al. | naacl | 2025-05-04 |
| 725 | FaithBench: A Diverse Hallucination Benchmark for Summarization By Modern LLMs Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper introduces FaithBench, a summarization hallucination benchmark comprising challenging hallucinations made by 10 modern LLMs from 8 different families, with ground truth annotations by human experts. |
FORREST SHENG BAO et. al. | naacl | 2025-05-04 |
| 726 | Reversed Attention: On The Gradient Descent Of Attention Layers In GPT Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we study the mathematics of the backward pass of attention, revealing that it implicitly calculates an attention matrix we refer to as “Reversed Attention”. |
Shahar Katz; Lior Wolf; | naacl | 2025-05-04 |
| 727 | CultureInstruct: Curating Multi-Cultural Instructions at Scale Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Large language models, despite their remarkable success in recent years, still exhibit severe cultural bias. Therefore, in this paper, we introduce CultureInstruct, a large-scale instruction-tuning dataset designed to reduce cultural bias in LLMs. |
Viet Thanh Pham; Zhuang Li; Lizhen Qu; Gholamreza Haffari; | naacl | 2025-05-04 |
| 728 | Making Language Models Robust Against Negation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a self-supervised method to make language models more robust against negation. |
MohammadHossein Rezaei; Eduardo Blanco; | naacl | 2025-05-04 |
| 729 | Stronger Universal and Transferable Attacks By Suppressing Refusals Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Contrary to this belief, we find that the adversarial prompts discovered by such optimizers are inherently prompt-universal and transferable, even when optimized on a single model and a single harmful request. To further exploit this phenomenon, we introduce IRIS, a new objective to these optimizers to explicitly deactivate the safety feature to create an even stronger universal and transferable attack. |
David Huang; Avidan Shah; Alexandre Araujo; David Wagner; Chawin Sitawarin; | naacl | 2025-05-04 |
| 730 | Emergence of Episodic Memory in Transformers: Characterizing Changes in Temporal Structure of Attention Scores During Training Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We investigate in-context temporal biases in attention heads and transformer outputs. |
Deven Mahesh Mistry; Anooshka Bajaj; Yash Aggarwal; Sahaj Singh Maini; Zoran Tiganj; | naacl | 2025-05-04 |
| 731 | On The Analysis and Distillation of Emergent Outlier Properties in Pre-trained Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We show that emergent outlier dimensions contribute significantly more to zero-shot performance than non-outlier dimensions. Based on this, we propose the Emergent Outlier Focused Distillation (EOFD) method, which prioritizes critical outlier dimensions in distillation using a weighted MSE loss. |
TIANYANG ZHAO et. al. | naacl | 2025-05-04 |
| 732 | Analyzing Memorization in Large Language Models Through The Lens of Model Attribution Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Existing research has mainly focused on post-hoc analyses—such as extracting memorized content or developing memorization metrics—without exploring the underlying architectural factors that contribute to memorization. In this work, we investigate memorization from an architectural lens by analyzing how attention modules at different layers impact its memorization and generalization performance. |
Tarun Ram Menta; Susmit Agrawal; Chirag Agarwal; | naacl | 2025-05-04 |
| 733 | Semantic Intelligence: Integrating GPT-4 with A Planning in Low-Cost Robotics Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work highlights how affordable robots can exhibit intelligent, context-aware behaviors by leveraging large language model reasoning with minimal hardware and no fine-tuning. |
Jesse Barkley; Abraham George; Amir Barati Farimani; | arxiv-cs.RO | 2025-05-03 |
| 734 | Good News for Script Kiddies? Evaluating Large Language Models for Automated Exploit Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To mitigate dataset bias, we introduce a benchmark with refactored versions of five software security labs. |
David Jin; Qian Fu; Yuekang Li; | arxiv-cs.CR | 2025-05-02 |
| 735 | Interpretable Spatial-Temporal Fusion Transformers: Multi-Output Prediction for Parametric Dynamical Systems with Time-Varying Inputs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We explore the promising performance of a transformer model in predicting outputs of parametric dynamical systems with external time-varying input signals. |
Shuwen Sun; Lihong Feng; Peter Benner; | arxiv-cs.LG | 2025-05-01 |
| 736 | Dual Filter: A Mathematical Framework for Inference Using Transformer-like Architectures Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a mathematical framework for causal nonlinear prediction in settings where observations are generated from an underlying hidden Markov model (HMM). |
Heng-Sheng Chang; Prashant G. Mehta; | arxiv-cs.LG | 2025-05-01 |
| 737 | GPT-Driven Gestures: Leveraging Large Language Models to Generate Expressive Robot Motion for Enhanced Human-Robot Interaction Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Expressive robot motion is a form of nonverbal communication that enables robots to convey their internal states, fostering effective human-robot interaction. A key step in … |
Liam Roy; Elizabeth A. Croft; Alex Ramirez; Dana Kulić; | IEEE Robotics and Automation Letters | 2025-05-01 |
| 738 | Building Privacy-Preserving Medical Text Models With A Pretrained Transformer Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The rapid advancement of big data and artificial intelligence (AI) in healthcare heightens the urgency for accurate medical text sentiment analysis. The privacy protection of … |
MUHAMMAD SHAFIQ et. al. | IEEE Internet of Things Journal | 2025-05-01 |
| 739 | Large Language Model-Driven Dynamic Assessment of Grammatical Accuracy in English Language Learner Writing Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study investigates the potential for Large Language Models (LLMs) to scale-up Dynamic Assessment (DA). |
Timur Jaganov; John Blake; Julián Villegas; Nicholas Carr; | arxiv-cs.CL | 2025-05-01 |
| 740 | Paths-over-Graph: Knowledge Graph Empowered Large Language Model Reasoning IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, existing KG-based LLM reasoning methods face challenges like handling multi-hop reasoning, multi-entity questions, and effectively utilizing graph structures. To address these issues, we propose Paths-over-Graph (PoG), a novel method that enhances LLM reasoning by integrating knowledge reasoning paths from KGs, improving the interpretability and faithfulness of LLM outputs. |
XINGYU TAN et. al. | www | 2025-04-30 |
| 741 | Enhancing Security and Strengthening Defenses in Automated Short-Answer Grading Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Our research identifies three main types of gaming strategies that exploit the system’s weaknesses, potentially leading to false positives. To counteract these vulnerabilities, we implement several adversarial training methods designed to enhance the systems’ robustness. |
SAHAR YARMOHAMMADTOOSKY et. al. | arxiv-cs.CL | 2025-04-30 |
| 742 | Entropy Heat-Mapping: Localizing GPT-Based OCR Errors with Sliding-Window Shannon Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present an entropy-heat-mapping proof-of-concept that turns per-token Shannon entropy into a visual ”uncertainty landscape”. |
Alexei Kaltchenko; | arxiv-cs.CV | 2025-04-30 |
| 743 | Triangle Matters! TopDyG: Topology-aware Transformer for Link Prediction on Dynamic Graphs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Recent Transformer-based link prediction methods on dynamic graphs not only fail to model the fine-grained structures such as triangles with the vanilla Transformers in the graph serialization process, but also amplify the imbalanced distribution of graphs because of their over-estimation of high-degree nodes. To tackle these issues, we propose a Topology-aware Transformer on Dynamic Graph (TopDyG) for link prediction, consisting of a topology injected Transformer (Ti-Transformer) and a mutual information learning (Mi-Learning). |
XIN ZHANG et. al. | www | 2025-04-30 |
| 744 | When Large Vision Language Models Meet Multimodal Sequential Recommendation: An Empirical Study Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, their application in multimodal sequential recommendation (MSR) has not been extensively studied. To bridge this gap, we introduce MSRBench, the first comprehensive benchmark designed to systematically evaluate different LVLM integration strategies in web-based recommendation scenarios. |
PEILIN ZHOU et. al. | www | 2025-04-30 |
| 745 | Why Compress What You Can Generate? When GPT-4o Generation Ushers in Image Compression Fields Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we investigate two typical compression paradigms: textual coding and multimodal coding (i.e., text + extremely low-resolution image), where all/most pixel-level information is generated instead of compressing via the advanced GPT-4o image generation function. |
Yixin Gao; Xiaohan Pan; Xin Li; Zhibo Chen; | arxiv-cs.CV | 2025-04-30 |
| 746 | Plant Disease Detection Through Multimodal Large Language Models and Convolutional Neural Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study investigates the effectiveness of combining multimodal Large Language Models (LLMs), specifically GPT-4o, with Convolutional Neural Networks (CNNs) for automated plant disease classification using leaf imagery. |
Konstantinos I. Roumeliotis; Ranjan Sapkota; Manoj Karkee; Nikolaos D. Tselikas; Dimitrios K. Nasiopoulos; | arxiv-cs.CV | 2025-04-29 |
| 747 | Leveraging Generative AI Through Prompt Engineering and Rigorous Validation to Create Comprehensive Synthetic Datasets for AI Training in Healthcare Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Access to high-quality medical data is often restricted due to privacy concerns, posing significant challenges for training artificial intelligence (AI) algorithms within Electronic Health Record (EHR) applications. In this study, prompt engineering with the GPT-4 API was employed to generate high-quality synthetic datasets aimed at overcoming this limitation. |
Polycarp Nalela; | arxiv-cs.AI | 2025-04-29 |
| 748 | JaccDiv: A Metric and Benchmark for Quantifying Diversity of Generated Marketing Text in The Music Industry Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we investigate LLM-based data-to-text approaches to automatically generate marketing texts that are of sufficient quality and diverse enough for broad adoption. |
Anum Afzal; Alexandre Mercier; Florian Matthes; | arxiv-cs.CL | 2025-04-29 |
| 749 | BrightCookies at SemEval-2025 Task 9: Exploring Data Augmentation for Food Hazard Classification Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose text augmentation techniques as a way to improve poor performance on minority classes and compare their effect for each category on various transformer and machine learning models. |
FOTEINI PAPADOPOULOU et. al. | arxiv-cs.CL | 2025-04-29 |
| 750 | Coreference Resolution for Vietnamese Narrative Texts Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This task is particularly challenging for Vietnamese, a low-resource language with limited annotated datasets. To address these challenges, we developed a comprehensive annotated dataset using narrative texts from VnExpress, a widely-read Vietnamese online news platform. |
Hieu-Dai Tran; Duc-Vu Nguyen; Ngan Luu-Thuy Nguyen; | arxiv-cs.CL | 2025-04-28 |
| 751 | Can LLMs Generate Higher Quality Code Than Humans? An Empirical Study Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Large Language Models are being extensively used for AI-assisted programming and code generation. The challenge is to ensure that the generated code is not only functionally … |
Mohammad Talal Jamil; Shamsa Abid; S. Shamail; | 2025 IEEE/ACM 22nd International Conference on Mining … | 2025-04-28 |
| 752 | Llama-3.1-FoundationAI-SecurityLLM-Base-8B Technical Report IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, their adoption in cybersecurity remains limited due to challenges like scarcity of specialized training data and complexity of representing cybersecurity-specific knowledge. To address these gaps, we present Foundation-Sec-8B, a cybersecurity-focused LLM built on the Llama 3.1 architecture and enhanced through continued pretraining on a carefully curated cybersecurity corpus. |
PAUL KASSIANIK et. al. | arxiv-cs.CR | 2025-04-28 |
| 753 | LLM-Assisted Automated Deductive Coding of Dialogue Data: Leveraging Dialogue-Specific Characteristics to Enhance Contextual Understanding Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The novelty of our proposed framework is threefold: 1) We predict the code for an utterance based on dialogue-specific characteristics — communicative acts and communicative events — using separate prompts following the role prompts and chain-of-thoughts methods; 2) We engaged multiple LLMs including GPT-4-turbo, GPT-4o, DeepSeek in collaborative code prediction; 3) We leveraged the interrelation between events and acts to implement consistency checking using GPT-4o. |
Ying Na; Shihui Feng; | arxiv-cs.CL | 2025-04-28 |
| 754 | Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We evaluated their performance by comparing LLM-generated codes with human-generated codes from a peer-reviewed systematic review on assessment. |
Dandan Chen Kaptur; Yue Huang; Xuejun Ryan Ji; Yanhui Guo; Bradley Kaptur; | arxiv-cs.CL | 2025-04-28 |
| 755 | VIST-GPT: Ushering in The Era of Visual Storytelling with LLMs? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a novel approach that leverages recent advancements in multimodal models, specifically adapting transformer-based architectures and large multimodal models, for the visual storytelling task. |
Mohamed Gado; Towhid Taliee; Muhammad Memon; Dmitry Ignatov; Radu Timofte; | arxiv-cs.CL | 2025-04-27 |
| 756 | From Inductive to Deductive: LLMs-Based Qualitative Data Analysis in Requirements Engineering Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we explore the use of Large Language Models (LLMs), including GPT-4, Mistral, and LLaMA-2, to improve QDA tasks in RE. |
Syed Tauhid Ullah Shah; Mohamad Hussein; Ann Barcomb; Mohammad Moshirpour; | arxiv-cs.SE | 2025-04-27 |
| 757 | Evaluating The Ability of GPT-4o to Generate Verifiable Specifications in VeriFast Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Static verification is a powerful method for enhancing software quality, but it demands significant human labor and resources. This is particularly true of static verifiers that … |
MARILYN REGO et. al. | 2025 IEEE/ACM Second International Conference on AI … | 2025-04-27 |
| 758 | Why You Shouldn’t Fully Trust ChatGPT: A Synthesis of This AI Tool’s Error Rates Across Disciplines and The Software Engineering Lifecycle Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Context: ChatGPT and other large language models (LLMs) are widely used across healthcare, business, economics, engineering, and software engineering (SE). |
Vahid Garousi; | arxiv-cs.SE | 2025-04-26 |
| 759 | EDU-NER-2025: Named Entity Recognition in Urdu Educational Texts Using XLM-RoBERTa with X (formerly Twitter) Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To achieve this objective this study makes three key contributions. Firstly, we created a manually annotated dataset in the education domain, named EDU-NER-2025, which contains 13 unique most important entities related to education domain. |
FIDA ULLAH et. al. | arxiv-cs.CL | 2025-04-25 |
| 760 | Privacy Perceptions of Custom GPTs By Users and Creators Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: GPTs are customized LLM apps built on OpenAI’s large language model. Any individual or organization can use and create GPTs without needing programming skills. However, the rapid … |
Rongjun Ma; Caterina Maidhof; Juan Carlos Carrillo; Janne Lindqvist; Jose Such; | Proceedings of the 2025 CHI Conference on Human Factors in … | 2025-04-25 |
| 761 | Application and Optimization of Large Models Based on Prompt Tuning for Fact-Check-Worthiness Estimation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In response to the growing problem of misinformation in the context of globalization and informatization, this paper proposes a classification method for fact-check-worthiness estimation based on prompt tuning. |
Yinglong Yu; Hao Shen; Zhengyi Lyu; Qi He; | arxiv-cs.CL | 2025-04-25 |
| 762 | Optimising ChatGPT for Creativity in Literary Translation: A Case Study from English Into Dutch, Chinese, Catalan and Spanish Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study examines the variability of Chat-GPT machine translation (MT) outputs across six different configurations in four languages,with a focus on creativity in a literary text. |
Shuxiang Du; Ana Guerberof Arenas; Antonio Toral; Kyo Gerrits; Josep Marco Borillo; | arxiv-cs.CL | 2025-04-25 |
| 763 | Efficient Hate Speech Detection: Evaluating 38 Models from Traditional Methods to Transformers Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The proliferation of hate speech on social media necessitates automated detection systems that balance accuracy with computational efficiency. This study evaluates 38 model … |
Mahmoud Abusaqer; Jamil Saquer; Hazim Shatnawi; | Proceedings of the 2025 ACM Southeast Conference | 2025-04-24 |
| 764 | FinBERT-QA: Financial Question Answering with Pre-trained BERT Language Models Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: Motivated by the emerging demand in the financial industry for the automatic analysis of unstructured and structured data at scale, Question Answering (QA) systems can provide … |
Bithiah Yuan; | ArXiv | 2025-04-24 |
| 765 | Optimism, Expectation, or Sarcasm? Multi-Class Hope Speech Detection in Spanish and English Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study introduces PolyHope V2, a multilingual, fine-grained hope speech dataset comprising over 30,000 annotated tweets in English and Spanish. |
SABUR BUTT et. al. | arxiv-cs.CL | 2025-04-24 |
| 766 | Ustnlp16 at SemEval-2025 Task 9: Improving Model Performance Through Imbalance Handling and Focal Loss Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Classification tasks often suffer from imbal- anced data distribution, which presents chal- lenges in food hazard detection due to severe class imbalances, short and unstructured text, and overlapping semantic categories. In this paper, we present our system for SemEval- 2025 Task 9: Food Hazard Detection, which ad- dresses these issues by applying data augmenta- tion techniques to improve classification perfor- mance. |
Zhuoang Cai; Zhenghao Li; Yang Liu; Liyuan Guo; Yangqiu Song; | arxiv-cs.CL | 2025-04-24 |
| 767 | Beyond Public Access in LLM Pre-Training Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Using a legally obtained dataset of 34 copyrighted O’Reilly Media books, we apply the DE-COP membership inference attack method to investigate whether OpenAI’s large language models were trained on copyrighted content without consent. |
Sruly Rosenblat; Tim O’Reilly; Ilan Strauss; | arxiv-cs.CL | 2025-04-24 |
| 768 | Beyond The Surface: Stylometric Analysis of GPT-4o’s Capacity for Literary Style Imitation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This study aims to explore the ability of GPT-4o to imitate the literary style of renowned authors. Ernest Hemingway and Mary Shelley were selected due to their contrasting … |
Georgios Mikros; | Digit. Scholarsh. Humanit. | 2025-04-23 |
| 769 | Towards Explainable AI: Multi-Modal Transformer for Video-based Image Description Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The proposed work introduces a novel framework for generating natural language descriptions from video datasets by combining textual and visual modalities. |
Lakshita Agarwal; Bindu Verma; | arxiv-cs.CV | 2025-04-23 |
| 770 | Tri-FusionNet: Enhancing Image Description Generation with Transformer-based Fusion Network and Dual Attention Mechanism Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose Tri-FusionNet, a novel image description generation model that integrates transformer modules: a Vision Transformer (ViT) encoder module with dual-attention mechanism, a Robustly Optimized BERT Approach (RoBERTa) decoder module, and a Contrastive Language-Image Pre-Training (CLIP) integrating module. |
Lakshita Agarwal; Bindu Verma; | arxiv-cs.CV | 2025-04-23 |
| 771 | Amplified Vulnerabilities: Structured Jailbreak Attacks on LLM-based Multi-Agent Debate Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce a novel structured prompt-rewriting framework specifically designed to exploit MAD dynamics via narrative encapsulation, role-driven escalation, iterative refinement, and rhetorical obfuscation. |
SENMAO QI et. al. | arxiv-cs.CR | 2025-04-23 |
| 772 | Durghotona GPT: A Web Scraping and Large Language Model Based Framework to Generate Road Accident Dataset Automatically in Bangladesh Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a novel framework named ‘Durghotona GPT’ that integrates web scraping and Large Language Models (LLMs) to automate the generation of comprehensive accident datasets from prominent national dailies in Bangladesh. |
MD Thamed Bin Zaman Chowdhury; Moazzem Hossain; Md. Ridwanul Islam; | arxiv-cs.CL | 2025-04-23 |
| 773 | Benchmarking LLM for Code Smells Detection: OpenAI GPT-4.0 Vs DeepSeek-V3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Determining the most effective Large Language Model for code smell detection presents a complex challenge. This study introduces a structured methodology and evaluation matrix to tackle this issue, leveraging a curated dataset of code samples consistently annotated with known smells. |
Ahmed R. Sadik; Siddhata Govind; | arxiv-cs.SE | 2025-04-22 |
| 774 | Transformer-Based Extraction of Statutory Definitions from The U.S. Code Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present an advanced NLP system leveraging transformer-based architectures to automatically extract defined terms, their definitions, and their scope from the U.S.C. |
Arpana Hosabettu; Harsh Shah; | arxiv-cs.CL | 2025-04-22 |
| 775 | Comparing Different Transformer Model Structures for Stock Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study aims to identify which Transformer variant is most suitable for stock forecasting. |
Qizhao Chen; | arxiv-cs.CE | 2025-04-22 |
| 776 | Exploring Next Token Prediction in Theory of Mind (ToM) Tasks: Comparative Experiments with GPT-2 and LLaMA-2 AI Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Language models have made significant progress in generating coherent text and predicting next tokens based on input prompts. |
Pavan Yadav; Nikhil Khandalkar; Krishna Shinde; Lokesh B. Ramegowda; Rajarshi Das; | arxiv-cs.CL | 2025-04-22 |
| 777 | Performance Evaluation of Emotion Classification in Japanese Using RoBERTa and DeBERTa Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Objective This study aims to build a high-accuracy model for predicting the presence or absence of eight Plutchik emotions in Japanese sentences. |
Yoichi Takenaka; | arxiv-cs.CL | 2025-04-22 |
| 778 | Support Evaluation for The TREC 2024 RAG Track: Comparing Human Versus LLM Judges Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: A crucial factor in RAG evaluation is support, whether the information in the cited documents supports the answer. |
NANDAN THAKUR et. al. | arxiv-cs.CL | 2025-04-21 |
| 779 | The Synthetic Imputation Approach: Generating Optimal Synthetic Texts For Underrepresented Categories In Supervised Classification Tasks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, it is often difficult to find sufficient examples for all categories in a task when building a high-quality training set. In this article, I describe this problem and propose a solution, the synthetic imputation approach. |
Joan C. Timoneda; | arxiv-cs.CL | 2025-04-21 |
| 780 | On Dimension-Free Transformer: An Application of STP to AI Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Using projection-based transformation of hypervector (PBTH), the framework of dimension-free transformer (DFT) is proposed by verifying each linear transformation in a transformer and replacing it by a proper PBTH, which allows the inputs and outputs being of arbitrary dimensions. |
Daizhan Cheng; | arxiv-cs.LG | 2025-04-20 |
| 781 | Quantitative Clustering in Mean-Field Transformer Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we investigate the long-time clustering of mean-field transformer models. |
Shi Chen; Zhengjiang Lin; Yury Polyanskiy; Philippe Rigollet; | arxiv-cs.LG | 2025-04-20 |
| 782 | Enhancing Multilingual Sentiment Analysis with Explainability for Sinhala, English, and Code-Mixed Content Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This research develops a hybrid aspect-based sentiment analysis framework that enhances multilingual capabilities with explainable outputs. |
AZMARAH RIZVI et. al. | arxiv-cs.CL | 2025-04-18 |
| 783 | One Jump Is All You Need: Short-Cutting Transformers for Early Exit Prediction with One Jump to Fit All Exit Levels Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose selection of a single One-Jump-Fits-All (OJFA) low-rank shortcut that offers over a 30x reduction in shortcut parameter costs during inference. |
Amrit Diggavi Seshadri; | arxiv-cs.LG | 2025-04-18 |
| 784 | SSTAF: Spatial-Spectral-Temporal Attention Fusion Transformer for Motor Imagery Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces a novel Spatial-Spectral-Temporal Attention Fusion (SSTAF) Transformer specifically designed for upper-limb motor imagery classification. |
Ummay Maria Muna; Md. Mehedi Hasan Shawon; Md Jobayer; Sumaiya Akter; Saifur Rahman Sabuj; | arxiv-cs.CV | 2025-04-17 |
| 785 | An Empirical Study of Python Library Migration Using Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: LargeLanguage Models (LLMs) are shown to be effective at generating and transformingcode as well as finding similar code, which are necessary upstream tasks forlibrary migration. |
Md Mohayeminul Islam; Ajay Kumar Jha; May Mahmoud; Ildar Akhmetov; Sarah Nadi; | arxiv-cs.SE | 2025-04-17 |
| 786 | Using Customized GPT to Develop Prompting Proficiency in Architectural AI-generated Images Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This research investigates the use of customized GPT models to enhance prompting proficiency among architecture students when generating AI-driven images. |
Juan David Salazar Rodriguez; Sam Conrad Joyce; | arxiv-cs.HC | 2025-04-16 |
| 787 | Adapting A World Model for Trajectory Following in A 3D Game Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we apply Inverse Dynamics Models (IDM) with different encoders and policy heads to trajectory following in a modern 3D video game — Bleeding Edge. |
MARKO TOT et. al. | arxiv-cs.AI | 2025-04-16 |
| 788 | The Impact of Decorrelation on Transformer Interpretation Methods: Applications to Clinical Speech AI Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study investigated the impact of two decorrelation methods on interpreting the decision-making logic of a Bidirectional Encoder Representations from Transformers (BERT) model. |
L. Xu; K. D. Mueller; J. Liss; V. Berisha; | icassp | 2025-04-15 |
| 789 | Using Corrected ASR Projection to Improve AD Recognition Performance from Spontaneous Speech Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, Automatic Speech Recognition transcription errors, stemming from language impairments in AD and Mild Cognitive Impairment patients, can lead to information loss during feature extraction. To mitigate this, we introduce the Corrected ASR Projecting, CAP model. |
Y. ZHANG et. al. | icassp | 2025-04-15 |
| 790 | SPT: Sequence Prompt Transformer for Interactive Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, existing methods typically process one image at a time, failing to consider the sequential nature of the images. To overcome this limitation, we propose a novel method called Sequence Prompt Transformer (SPT), the first to utilize sequential image information for interactive segmentation. |
S. Cheng; | icassp | 2025-04-15 |
| 791 | Transitive Inference in Large Language Models and Prompting Intervention Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Two prompting methods — Model Confidence prompts (likelihood tests) and Chain-of-Thought prompts—are applied in order to further enhance TI performance. |
W. Wu; W. Deng; | icassp | 2025-04-15 |
| 792 | GPT-C: Generative PrompT Compression Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To this end, we propose a Generative PrompT Compression (GPT-C) paradigm. |
L. Liu; R. Wang; L. Jing; F. Lv; Z. Zhu; | icassp | 2025-04-15 |
| 793 | Making Acoustic Side-Channel Attacks on Noisy Keyboards Viable with LLM-Assisted Spectrograms’ Typo Correction Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we demonstrate that both strategies are viable and complementary solutions for making ASCAs practical. |
Seyyed Ali Ayati; Jin Hyun Park; Yichen Cai; Marcus Botacin; | arxiv-cs.CR | 2025-04-15 |
| 794 | A Study on Zero-shot Non-intrusive Speech Assessment Using Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work investigates two strategies for zero-shot non-intrusive speech assessment leveraging large language models. |
R. E. Zezario; S. M. Siniscalchi; H. -M. Wang; Y. Tsao; | icassp | 2025-04-15 |
| 795 | SepMamba: State-Space Models for Speaker Separation Using Mamba Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose Sep-Mamba, a U-Net-based architecture composed of bidirectional Mamba layers. |
T. H. Avenstrup; | icassp | 2025-04-15 |
| 796 | Towards Interactive Deepfake Analysis Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper aims to explore interactive deepfake analysis by performing instruction tuning on multi-modal large language models (MLLMs). |
L. Qin; | icassp | 2025-04-15 |
| 797 | GPT-LAD: Leveraging Large Multimodal Models for Logical Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, no existing methods replicate the way humans set and compare against normality criteria to judge normality. To address this gap, we propose a novel framework that mimics human reasoning by defining normality criteria and leveraging GPT-4V’s advanced logical reasoning capabilities. |
Y. An; D. Kang; | icassp | 2025-04-15 |
| 798 | Adaptive Large Language Models Via Attention Shortcuts Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, these models simply stack the same blocks in dozens of layers and process information sequentially from one block to another. In this paper, we propose to challenge this and introduce adaptive computations for LLM-like setups, which allow the final layer to attend to all of the intermediate layers as it deems fit through the attention mechanism, thereby introducing computational attention shortcuts. |
P. Verma; M. Pilanci; | icassp | 2025-04-15 |
| 799 | VEXP: A Low-Cost RISC-V ISA Extension for Accelerated Softmax Computation in Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Accelerating Softmax is challenging due to its non-pointwise, non-linear nature, with exponentiation as the most demanding step. To address this, we design a custom arithmetic block for Bfloat16 exponentiation leveraging a novel approximation algorithm based on Schraudolph’s method, and we integrate it into the Floating-Point Unit (FPU) of the RISC-V cores of a compute cluster, through custom Instruction Set Architecture (ISA) extensions, with a negligible area overhead of 1\%. |
RUN WANG et. al. | arxiv-cs.AR | 2025-04-15 |
| 800 | Self-Enhanced Reasoning Training: Activating Latent Reasoning in Small Models for Enhanced Reasoning Distillation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Our observations reveal that small models can generate high-quality reasoning paths during sampling, even without chain-of-thought prompting, though these paths are often latent due to their low probability under standard decoding strategies. To address this, we propose Self-Enhanced Reasoning Training (SERT), which activates and leverages latent reasoning capabilities in small models through self-training on filtered, self-generated reasoning paths under zero-shot conditions. |
Y. Zhang; | icassp | 2025-04-15 |
| 801 | BP-GPT: Auditory Neural Decoding Using FMRI-prompted LLM Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce a novel method, the Brain Prompt GPT (BP-GPT). |
X. Chen; C. Du; C. Liu; Y. Wang; H. He; | icassp | 2025-04-15 |
| 802 | How Redundant Is The Transformer Stack in Speech Representation Models? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We perform a detailed analysis of layer similarity in speech representation models using three similarity metrics: cosine similarity, centered kernel alignment, and mutual nearest-neighbor alignment. |
T. Dorszewski; A. K. Jacobsen; L. Tětková; L. K. Hansen; | icassp | 2025-04-15 |
| 803 | Graph-Driven Multimodal Feature Learning Framework for Apparent Personality Assessment Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces an innovative multimodal feature learning framework for personality analysis in short video clips. |
Kangsheng Wang; Chengwei Ye; Huanzhen Zhang; Linuo Xu; Shuyan Liu; | arxiv-cs.CV | 2025-04-15 |
| 804 | SVTNet: Dual Branch of Swin Transformer and Vision Transformer for Monocular Depth Estimation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce a novel dual branch network called Swin Vision Transformer Net (SVTNet), where the Swin Transformer and Vision Transformer are combined to learn features with global and local information. |
S. Jia; Y. Wang; H. Chen; S. Huang; | icassp | 2025-04-15 |
| 805 | RefleXGen:The Unexamined Code Is Not Worth Using Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces RefleXGen, an innovative method that significantly enhances code security by integrating Retrieval-Augmented Generation (RAG) techniques with guided self-reflection mechanisms inherent in LLMs. |
B. Wang; | icassp | 2025-04-15 |
| 806 | Paging Dr. GPT: Extracting Information from Clinical Notes to Enhance Patient Predictions Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we investigate how answers generated by GPT-4o-mini (ChatGPT) to simple clinical questions about patients, when given access to the patient’s discharge summary, can support patient-level mortality prediction. |
David Anderson; Michaela Anderson; Margret Bjarnadottir; Stephen Mahar; Shriyan Reyya; | arxiv-cs.CL | 2025-04-14 |
| 807 | TWSSenti: A Novel Hybrid Framework for Topic-Wise Sentiment Analysis on Social Media Using Transformer Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study explores a hybrid framework combining transformer-based models, specifically BERT, GPT-2, RoBERTa, XLNet, and DistilBERT, to improve sentiment classification accuracy and robustness. |
Aish Albladi; Md Kaosar Uddin; Minarul Islam; Cheryl Seals; | arxiv-cs.CL | 2025-04-14 |
| 808 | Keyword Extraction, and Aspect Classification in Sinhala, English, and Code-Mixed Content Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study introduces a hybrid NLP method to improve keyword extraction, content filtering, and aspect-based classification of banking content. |
F. A. RIZVI et. al. | arxiv-cs.CL | 2025-04-14 |
| 809 | Hallucination-Aware Generative Pretrained Transformer for Cooperative Aerial Mobility Control Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes SafeGPT, a two-tiered framework that integrates generative pretrained transformers (GPTs) with reinforcement learning (RL) for efficient and reliable unmanned aerial vehicle (UAV) last-mile deliveries. |
HYOJUN AHN et. al. | arxiv-cs.AI | 2025-04-14 |
| 810 | LITERA: An LLM Based Approach to Latin-to-English Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces an LLM-based Latin-to-English translation platform designed to address the challenges of translating Latin texts. |
Paul Rosu; | arxiv-cs.CL | 2025-04-14 |
| 811 | ClinicalGPT-R1: Pushing Reasoning Capability of Generalist Disease Diagnosis with Large Language Model Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Here, we introduce ClinicalGPT-R1, a reasoning enhanced generalist large language model for disease diagnosis. |
WUYANG LAN et. al. | arxiv-cs.CL | 2025-04-13 |
| 812 | D$^2$iT: Dynamic Diffusion Transformer for Accurate Image Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, large compression leads to limited local realism, while small compression increases computational complexity and compromises global consistency, ultimately impacting the quality of generated images. To address these limitations, we propose dynamically compressing different image regions by recognizing the importance of different regions, and introduce a novel two-stage framework designed to enhance the effectiveness and efficiency of image generation: (1) Dynamic VAE (DVAE) at first stage employs a hierarchical encoder to encode different image regions at different downsampling rates, tailored to their specific information densities, thereby providing more accurate and natural latent codes for the diffusion process. |
Weinan Jia; Mengqi Huang; Nan Chen; Lei Zhang; Zhendong Mao; | arxiv-cs.CV | 2025-04-13 |
| 813 | D2iT: Dynamic Diffusion Transformer for Accurate Image Generation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Diffusion models are widely recognized for their ability to generate high-fidelity images. Despite the excellent performance and scalability of the Diffusion Transformer (DiT) … |
Wei Jia; Mengqi Huang; Nan Chen; Lei Zhang; Zhendong Mao; | 2025 IEEE/CVF Conference on Computer Vision and Pattern … | 2025-04-13 |
| 814 | Composable NLP Workflows for BERT-based Ranking and QA System Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we built an end-to-end Ranking and Question-Answering (QA) system using Forte, a toolkit that makes composable NLP pipelines. |
Gaurav Kumar; Murali Mohana Krishna Dandu; | arxiv-cs.CL | 2025-04-12 |
| 815 | Generating Planning Feedback for Open-Ended Programming Exercises with LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To this end, we propose an approach that detects which high-level goals and patterns (i.e. programming plans) exist in a student program with LLMs. |
Mehmet Arif Demirtaş; Claire Zheng; Max Fowler; Kathryn Cunningham; | arxiv-cs.CL | 2025-04-11 |
| 816 | SWAN-GPT: An Efficient and Scalable Approach for Long-Context Language Modeling Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Overall, our work presents an effective approach for scaling language models to longer contexts in a robust and efficient manner. |
KRISHNA C. PUVVADA et. al. | arxiv-cs.CL | 2025-04-11 |
| 817 | ModernBERT or DeBERTaV3? Examining Architecture and Data Influence on Transformer Encoder Models Performance Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we conduct a controlled study by pretraining ModernBERT on the same dataset as CamemBERTaV2, a DeBERTaV3 French model, isolating the effect of model design. |
Wissam Antoun; Benoît Sagot; Djamé Seddah; | arxiv-cs.CL | 2025-04-11 |
| 818 | Examining GPT’s Capability to Generate and Map Course Concepts and Their Relationship Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper investigates the potential of LLMs such as GPT in automatically generating course concepts and their relations. |
TIANYUAN YANG et. al. | arxiv-cs.CY | 2025-04-11 |
| 819 | Does GPT Really Get It? A Hierarchical Scale to Quantify Human and AI’s Understanding of Algorithms Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: As Large Language Models (LLMs) are used for increasingly complex cognitive tasks, a natural question is whether AI really understands. The study of understanding in LLMs is in … |
Mirabel Reid; S. Vempala; | AAAI Conference on Artificial Intelligence | 2025-04-11 |
| 820 | Has The Creativity of Large-Language Models Peaked? An Analysis of Inter- and Intra-LLM Variability Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we evaluated 14 widely used LLMs — including GPT-4, Claude, Llama, Grok, Mistral, and DeepSeek — across two validated creativity assessments: the Divergent Association Task (DAT) and the Alternative Uses Task (AUT). |
Jennifer Haase; Paul H. P. Hanel; Sebastian Pokutta; | arxiv-cs.CL | 2025-04-10 |
| 821 | Beyond LLMs: A Linguistic Approach to Causal Graph Generation from Narrative Texts Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a novel framework for generating causal graphs from narrative texts, bridging high-level causality and detailed event-specific relationships. |
Zehan Li; Ruhua Pan; Xinyu Pi; | arxiv-cs.CL | 2025-04-10 |
| 822 | VL-Rethinker: Incentivizing Self-Reflection of Vision-Language Models with Reinforcement Learning IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View 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. | arxiv-cs.LG | 2025-04-10 |
| 823 | A Unified Agentic Framework for Evaluating Conditional Image Generation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper introduces CIGEval, a unified agentic framework for comprehensive evaluation of conditional image generation tasks. |
JIFANG WANG et. al. | arxiv-cs.CV | 2025-04-09 |
| 824 | Have We Unified Image Generation and Understanding Yet? An Empirical Study of GPT-4o’s Image Generation Ability Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: OpenAI’s multimodal GPT-4o has demonstrated remarkable capabilities in image generation and editing, yet its ability to achieve world knowledge-informed semantic synthesis–seamlessly integrating domain knowledge, contextual reasoning, and instruction adherence–remains unproven. In this study, we systematically evaluate these capabilities across three critical dimensions: (1) Global Instruction Adherence, (2) Fine-Grained Editing Precision, and (3) Post-Generation Reasoning. |
Ning Li; Jingran Zhang; Justin Cui; | arxiv-cs.CV | 2025-04-09 |
| 825 | A Temporal Scale Transformer Framework for Precise Remaining Useful Life Prediction in Fuel Cells Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: It also faces challenges in capturing both global long-term dependencies and local details effectively. To tackle this, we propose the Temporal Scale Transformer (TSTransformer), an enhanced version of the inverted Transformer (iTransformer). |
Zezhi Tang; Xiaoyu Chen; Xin Jin; Benyuan Zhang; Wenyu Liang; | arxiv-cs.LG | 2025-04-08 |
| 826 | An Empirical Study of GPT-4o Image Generation Capabilities IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we conduct an empirical study of GPT-4o’s image generation capabilities, benchmarking it against leading open-source and commercial models. |
SIXIANG CHEN et. al. | arxiv-cs.CV | 2025-04-08 |
| 827 | Towards Smarter Hiring: Are Zero-Shot and Few-Shot Pre-trained LLMs Ready for HR Spoken Interview Transcript Analysis? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This research paper presents a comprehensive analysis of the performance of prominent pre-trained large language models (LLMs), including GPT-4 Turbo, GPT-3.5 Turbo, text-davinci-003, text-babbage-001, text-curie-001, text-ada-001, llama-2-7b-chat, llama-2-13b-chat, and llama-2-70b-chat, in comparison to expert human evaluators in providing scores, identifying errors, and offering feedback and improvement suggestions to candidates during mock HR (Human Resources) interviews. |
Subhankar Maity; Aniket Deroy; Sudeshna Sarkar; | arxiv-cs.CL | 2025-04-08 |
| 828 | Leveraging Prompt-Tuning for Bengali Grammatical Error Explanation Using Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a novel three-step prompt-tuning method for Bengali Grammatical Error Explanation (BGEE) using state-of-the-art large language models (LLMs) such as GPT-4, GPT-3.5 Turbo, and Llama-2-70b. |
Subhankar Maity; Aniket Deroy; | arxiv-cs.CL | 2025-04-07 |
| 829 | What We Do Not Know: GPT Use in Business and Management Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The primary contribution of this paper is a call to action for further research. |
TAMMY MACKENZIE et. al. | arxiv-cs.CY | 2025-04-07 |
| 830 | Provable Failure of Language Models in Learning Majority Boolean Logic Via Gradient Descent Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we investigate whether Transformers can truly learn simple majority functions when trained using gradient-based methods. |
Bo Chen; Zhenmei Shi; Zhao Song; Jiahao Zhang; | arxiv-cs.LG | 2025-04-06 |
| 831 | Could AI Trace and Explain The Origins of AI-Generated Images and Text? Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Furthermore, whether AI systems like GPT-4o can explain why certain forged content is attributed to specific generative models is still an open question, with no existing benchmark addressing this. To fill this gap, we introduce AI-FAKER, a comprehensive multimodal dataset with over 280,000 samples spanning multiple LLMs and LMMs, covering both general and malicious use cases for AI-generated images and texts. |
HONGCHAO FANG et. al. | arxiv-cs.CL | 2025-04-05 |
| 832 | Geo-OLM: Enabling Sustainable Earth Observation Studies with Cost-Efficient Open Language Models & State-Driven Workflows Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present Geo-OLM, a tool-augmented geospatial agent that leverages the novel paradigm of state-driven LLM reasoning to decouple task progression from tool calling. |
Dimitrios Stamoulis; Diana Marculescu; | arxiv-cs.LG | 2025-04-05 |
| 833 | YaleNLP @ PerAnsSumm 2025: Multi-Perspective Integration Via Mixture-of-Agents for Enhanced Healthcare QA Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this study, we address the PerAnsSumm Shared Task using two complementary paradigms: (i) a training-based approach through QLoRA fine-tuning of LLaMA-3.3-70B-Instruct, and (ii) agentic approaches including zero- and few-shot prompting with frontier LLMs (LLaMA-3.3-70B-Instruct and GPT-4o) and a Mixture-of-Agents (MoA) framework that leverages a diverse set of LLMs by combining outputs from multi-layer feedback aggregation. |
Dongsuk Jang; Alan Li; Arman Cohan; | arxiv-cs.CL | 2025-04-04 |
| 834 | Can ChatGPT Learn My Life From A Week of First-Person Video? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Motivated by recent improvements in generative AI and wearable camera devices (e.g. smart glasses and AI-enabled pins), I investigate the ability of foundation models to learn about the wearer’s personal life through first-person camera data. |
Keegan Harris; | arxiv-cs.CV | 2025-04-04 |
| 835 | Efficient Dynamic Clustering-Based Document Compression for Retrieval-Augmented-Generation Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: Retrieval-Augmented Generation (RAG) has emerged as a widely adopted approachfor knowledge injection during large language model (LLM) inference in recentyears. However, due to … |
WEITAO LI et. al. | arxiv-cs.CL | 2025-04-04 |
| 836 | Structured Extraction of Process Structure Properties Relationships in Materials Science Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we introduce a novel annotation schema designed to extract generic process-structure-properties relationships from scientific literature. |
AMIT K VERMA et. al. | arxiv-cs.CL | 2025-04-04 |
| 837 | Neutralizing The Narrative: AI-Powered Debiasing of Online News Articles Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Here, we introduce an AI-driven framework leveraging advanced large language models (LLMs), specifically GPT-4o, GPT-4o Mini, Gemini Pro, Gemini Flash, Llama 8B, and Llama 3B, to systematically identify and mitigate biases in news articles. |
CHEN WEI KUO et. al. | arxiv-cs.CL | 2025-04-04 |
| 838 | Artificial Intelligence Application in Lymphoma Diagnosis: from Convolutional Neural Network to Vision Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Due to their promising feature detection, we aim to explore vision transformer models for diagnosis of anaplastic large cell lymphoma versus classical Hodgkin lymphoma using pathology whole slide images of HE slides. |
DANIEL RIVERA et. al. | arxiv-cs.CV | 2025-04-04 |
| 839 | Pivoted Low Resource Multilingual Translation with NER Optimization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Machine translation (MT) has advanced significantly with neural machine translation (NMT) models like BERT, GPT, and MarianMT, which leverage deep learning to provide more … |
Danang Arbian Sulistyo; D. D. Prasetya; Fadhli Almu’iini Ahda; Aji Prasetya Wibawa; | ACM Transactions on Asian and Low-Resource Language … | 2025-04-03 |
| 840 | GPT-ImgEval: A Comprehensive Benchmark for Diagnosing GPT4o in Image Generation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The recent breakthroughs in OpenAI’s GPT4o model have demonstrated surprisingly good capabilities in image generation and editing, resulting in significant excitement in the community. This technical report presents the first-look evaluation benchmark (named GPT-ImgEval), quantitatively and qualitatively diagnosing GPT-4o’s performance across three critical dimensions: (1) generation quality, (2) editing proficiency, and (3) world knowledge-informed semantic synthesis. |
ZHIYUAN YAN et. al. | arxiv-cs.CV | 2025-04-03 |
| 841 | AD-GPT: Large Language Models in Alzheimer’s Disease Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Large language models (LLMs) have emerged as powerful tools for medical information retrieval, yet their accuracy and depth remain limited in specialized domains such as Alzheimer’s disease (AD), a growing global health challenge. To address this gap, we introduce AD-GPT, a domain-specific generative pre-trained transformer designed to enhance the retrieval and analysis of AD-related genetic and neurobiological information. |
ZIYU LIU et. al. | arxiv-cs.CL | 2025-04-03 |
| 842 | Task As Context Prompting for Accurate Medical Symptom Coding Using Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Symptom coding, as tailored in this study, involves identifying and linking nuanced symptom mentions to standardized vocabularies like MedDRA, differentiating it from broader medical coding tasks. |
Chengyang He; Wenlong Zhang; Violet Xinying Chen; Yue Ning; Ping Wang; | arxiv-cs.CL | 2025-04-03 |
| 843 | Dual-stream Transformer-GCN Model with Contextualized Representations Learning for Monocular 3D Human Pose Estimation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper introduces a novel approach to monocular 3D human pose estimation using contextualized representation learning with the Transformer-GCN dual-stream model. |
MINGRUI YE et. al. | arxiv-cs.CV | 2025-04-02 |
| 844 | Subasa – Adapting Language Models for Low-resourced Offensive Language Detection in Sinhala Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Accurate detection of offensive language is essential for a number of applications related to social media safety. There is a sharp contrast in performance in this task between … |
Shanilka Haturusinghe; Tharindu Cyril Weerasooriya; Marcos Zampieri; C. Homan; S. R. Liyanage; | North American Chapter of the Association for Computational … | 2025-04-02 |
| 845 | Subasa — Adapting Language Models for Low-resourced Offensive Language Detection in Sinhala Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Using this approach, we introduce four models: Subasa-XLM-R, which incorporates an intermediate Pre-Finetuning step using Masked Rationale Prediction. |
Shanilka Haturusinghe; Tharindu Cyril Weerasooriya; Marcos Zampieri; Christopher M. Homan; S. R. Liyanage; | arxiv-cs.CL | 2025-04-02 |
| 846 | Compositional-ARC: Assessing Systematic Generalization in Abstract Spatial Reasoning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we extendmeta-learning for compositionality to the domain of abstract spatial reasoning.To this end, we introduce $\textit{Compositional-ARC}-$a dataset designed toevaluate the capacity of models to systematically generalize from knowngeometric transformations (e.g., translation, rotation) of abstracttwo-dimensional objects to novel combinations of these transformations (e.g.,translation+rotation). |
Philipp Mondorf; Shijia Zhou; Monica Riedler; Barbara Plank; | arxiv-cs.AI | 2025-04-02 |
| 847 | A Thorough Benchmark of Automatic Text Classification: From Traditional Approaches to Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Despite recent effectiveness improvements, a comprehensive cost-benefit analysis investigating whether the effectiveness gains of these recent approaches compensate their much higher costs when compared to more traditional text classification approaches such as SVMs and Logistic Regression is still missing in the literature. In this context, this work’s main contributions are twofold: (i) we provide a scientifically sound comparative analysis of the cost-benefit of twelve traditional and recent ATC solutions including five open LLMs, and (ii) a large benchmark comprising {22 datasets}, including sentiment analysis and topic classification, with their (train-validation-test) partitions based on folded cross-validation procedures, along with documentation, and code. |
Washington Cunha; Leonardo Rocha; Marcos André Gonçalves; | arxiv-cs.CL | 2025-04-02 |
| 848 | LLM-Assisted Proactive Threat Intelligence for Automated Reasoning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This research presents a novel approach to enhance real-time cybersecurity threat detection and response by integrating large language models (LLMs) and Retrieval-Augmented Generation (RAG) systems with continuous threat intelligence feeds. |
Shuva Paul; Farhad Alemi; Richard Macwan; | arxiv-cs.CR | 2025-04-01 |
| 849 | TST-Trans: A Transformer Network for Urban Traffic Flow Prediction Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: A critical challenge for predicting urban traffic flows is to simultaneously process time series and spatial features from heterogeneous traffic data collected by diverse Internet … |
KE ZHANG et. al. | IEEE Internet of Things Journal | 2025-04-01 |
| 850 | A Comparative Analysis on Using GPT and BERT for Automated Vulnerability Scoring Related Papers Related Patents Related Grants Related Venues Related Experts View |
Seyedeh Leili Mirtaheri; Andrea Pugliese; Narges Movahed; R. Shahbazian; | Intell. Syst. Appl. | 2025-04-01 |
| 851 | Semantic Adapter for Universal Text Embeddings: Diagnosing and Mitigating Negation Blindness to Enhance Universality Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To efficiently deal with the conflict thatdifferent tasks need different trade-offs between topic and negationinformation among other semantic information, a data-efficient andcomputational-efficient embedding re-weighting method is proposed withoutmodifying the parameters of text embedding models. |
Hongliu Cao; | arxiv-cs.CL | 2025-04-01 |
| 852 | Detecting PTSD in Clinical Interviews: A Comparative Analysis of NLP Methods and Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We compared general andmental health-specific transformer models (BERT/RoBERTa), embedding-basedmethods (SentenceBERT/LLaMA), and large language model prompting strategies(zero-shot/few-shot/chain-of-thought) using the DAIC-WOZ dataset.Domain-specific end-to-end models significantly outperformed general models(Mental-RoBERTa AUPRC=0.675+/-0.084 vs. RoBERTa-base 0.599+/-0.145). |
Feng Chen; Dror Ben-Zeev; Gillian Sparks; Arya Kadakia; Trevor Cohen; | arxiv-cs.CL | 2025-04-01 |
| 853 | XL-HQL: A HQL Query Generation Method Via XLNet and Column Attention Related Papers Related Patents Related Grants Related Venues Related Experts View |
Rongcun Wang; Yiqian Hou; Yuan Tian; Zhanqi Cui; Shujuan Jiang; | Inf. Softw. Technol. | 2025-04-01 |
| 854 | AGBN-Transformer: Anatomy-guided Brain Network Transformer for Schizophrenia Diagnosis Related Papers Related Patents Related Grants Related Venues Related Experts View |
Jiashuang Huang; Mingliang Wang; Hengrong Ju; Weiping Ding; Daoqiang Zhang; | Biomed. Signal Process. Control. | 2025-04-01 |
| 855 | UnrealMentor GPT: A System for Teaching Programming Based on A Large Language Model Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This paper introduces UnrealMentor GPT, a multiagent debugging framework that combines advanced large language model (LLM) capabilities with a dynamically updated knowledge base. … |
Hongli Zhu; Jian Xiang; Zhichuang Yang; | Computer Applications in Engineering Education | 2025-03-31 |
| 856 | LLM4FS: Leveraging Large Language Models for Feature Selection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Recent advances in large language models (LLMs) have provided newopportunities for decision-making, particularly in the task of automatedfeature selection. In this paper, we first … |
Jianhao Li; Xianchao Xiu; | arxiv-cs.LG | 2025-03-31 |
| 857 | Do Large Language Models Contain Software Architectural Knowledge? : An Exploratory Case Study with GPT Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Architectural knowledge (AK) of existing systems is essential for software engineers to make design decisions. Recently, Large Language Models (LLMs) trained on large-scale … |
Mohamed Soliman; Jan Keim; | 2025 IEEE 22nd International Conference on Software … | 2025-03-31 |
| 858 | Accelerating High-Efficiency Organic Photovoltaic Discovery Via Pretrained Graph Neural Networks and Generative Reinforcement Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a framework that integrates large-scale pretraining of graph neural networks (GNNs) with a GPT-2 (Generative Pretrained Transformer 2)-based reinforcement learning (RL) strategy to design OPV molecules with potentially high PCE. |
JIANGJIE QIU et. al. | arxiv-cs.LG | 2025-03-31 |
| 859 | Multilingual Sentiment Analysis of Summarized Texts: A Cross-Language Study of Text Shortening Effects Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study examines extractive and abstractive summarization effects on sentiment classification in English, German, French, Spanish, Italian, Finnish, Hungarian, and Arabic. |
Mikhail Krasitskii; Grigori Sidorov; Olga Kolesnikova; Liliana Chanona Hernandez; Alexander Gelbukh; | arxiv-cs.CL | 2025-03-31 |
| 860 | Synthetic News Generation for Fake News Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The study highlights the potential of synthetic data to enhance fake news detection systems, offering valuable insights for future research and suggesting that targeted improvements in synthetic data generation can further strengthen detection models. |
Abdul Sittar; Luka Golob; Mateja Smiljanic; | arxiv-cs.CL | 2025-03-31 |
| 861 | Comparing Representations of Long Clinical Texts for The Task of Patient Note-identification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we address the challenge of patient-note identification, which involves accurately matching an anonymized clinical note to its corresponding patient, represented by a set of related notes. |
SAFA ALSAIDI et. al. | arxiv-cs.CL | 2025-03-31 |
| 862 | Fine-Tuning GPT-3.5-Turbo for Automatic Feedback Generation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Scaling up the delivery of effective feedback remains an open challenge in education. Existing automatic feedback generation (AFG) methods fall short in providing feedback highly … |
Elisabetta Mazzullo; Okan Bulut; Cole Walsh; G. Sitarenios; Alexander MacIntosh; | Proceedings of the 40th ACM/SIGAPP Symposium on Applied … | 2025-03-31 |
| 863 | Adaptive Test Healing Using LLM/GPT and Reinforcement Learning Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Flaky tests disrupt software development pipelines by producing inconsistent results, undermining reliability and efficiency. This paper introduces a hybrid framework for adaptive … |
Nariman Mani; Salma Attaranasl; | 2025 IEEE International Conference on Software Testing, … | 2025-03-31 |
| 864 | Text Chunking for Document Classification for Urban System Management Using Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The novel contributions of this paper lie in assessing the performance of OpenAI GPT models and introduces the chunk-based prompting approach, which addresses context aggregation biases by preserving localized context. |
Joshua Rodriguez; Om Sanan; Guillermo Vizarreta-Luna; Steven A. Conrad; | arxiv-cs.CL | 2025-03-31 |
| 865 | The Cursive Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: But handwriting data, represented as sequences of pen coordinates, remains underexplored. We introduce a novel tokenization scheme that converts pen stroke offsets to polar coordinates, discretizes them into bins, and then turns them into sequences of tokens with which to train a standard GPT model. |
Sam Greydanus; Zachary Wimpee; | arxiv-cs.LG | 2025-03-30 |
| 866 | Measuring Online Hate on 4chan Using Pre-trained Deep Learning Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work focuses on analysing and measuring the prevalence of online hate on 4chan’s politically incorrect board (/pol/) using state-of-the-art Natural Language Processing (NLP) models, specifically transformer-based models such as RoBERTa and Detoxify. By leveraging these advanced models, we provide an in-depth analysis of hate speech dynamics and quantify the extent of online hate non-moderated platforms. |
Adrian Bermudez-Villalva; Maryam Mehrnezhad; Ehsan Toreini; | arxiv-cs.CL | 2025-03-30 |
| 867 | Large Language Models Pass The Turing Test IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We evaluated 4 systems (ELIZA, GPT-4o, LLaMa-3.1-405B, and GPT-4.5) in two randomised, controlled, and pre-registered Turing tests on independent populations. |
Cameron R. Jones; Benjamin K. Bergen; | arxiv-cs.CL | 2025-03-30 |
| 868 | AI Delivers Creative Output But Struggles with Thinking Processes Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study examined whether AI models (GPT-3.5-turbo, GPT-4, and GPT-4o) engage in creative thinking by comparing their performance with humans across various creative tasks and core cognitive processes. |
MAN ZHANG et. al. | arxiv-cs.HC | 2025-03-30 |
| 869 | Exploring GPT-4 for Robotic Agent Strategy with Real-Time State Feedback and A Reactive Behaviour Framework Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a method that successfully addresses practical concerns around safety, transitions between tasks, time horizons of tasks and state feedback. |
Thomas O’Brien; Ysobel Sims; | arxiv-cs.RO | 2025-03-30 |
| 870 | Advancing Sentiment Analysis in Tamil-English Code-Mixed Texts: Challenges and Transformer-Based Solutions Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The sentiment analysis task in Tamil-English code-mixed texts has been explored using advanced transformer-based models. |
Mikhail Krasitskii; Olga Kolesnikova; Liliana Chanona Hernandez; Grigori Sidorov; Alexander Gelbukh; | arxiv-cs.CL | 2025-03-29 |
| 871 | XL-Suite: Cross-Lingual Synthetic Training and Evaluation Data for Open-Ended Generation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Cross-lingual open-ended generation – responding in a language different fromthat of the query – is an important yet understudied problem. This workproposes XL-Instruct, a novel … |
Vivek Iyer; Pinzhen Chen; Ricardo Rei; Alexandra Birch; | arxiv-cs.CL | 2025-03-29 |
| 872 | Integrating Artificial Intelligence with Human Expertise: An In-depth Analysis of ChatGPT’s Capabilities in Generating Metamorphic Relations Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Context: This paper provides an in-depth examination of the generation and evaluation of Metamorphic Relations (MRs) using GPT models developed by OpenAI, with a particular focus on the capabilities of GPT-4 in software testing environments. |
YIFAN ZHANG et. al. | arxiv-cs.SE | 2025-03-28 |
| 873 | Multimodal Machine Learning with Large Language Embedding Model for Polymer Property Prediction Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Contemporary large language models (LLMs), such as GPT-4 and Llama, have harnessed extensive computational power and diverse text corpora to achieve remarkable proficiency in interpreting and generating domain-specific content, including materials science. To leverage the domain knowledge embedded within these models, we propose a simple yet effective multimodal architecture, PolyLLMem, which integrates text embeddings generated by Llama 3 with molecular structure embeddings derived from Uni-Mol, for polymer properties prediction tasks. |
Tianren Zhang; Dai-Bei Yang; | arxiv-cs.LG | 2025-03-28 |
| 874 | ViSketch-GPT: Collaborative Multi-Scale Feature Extraction for Sketch Recognition and Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Recognizing complex structural patterns improves both the accuracy in recognizing sketches and the fidelity of the generated sketches. In this work, we introduce ViSketch-GPT, a novel algorithm designed to address these challenges through a multi-scale context extraction approach. |
Giulio Federico; Giuseppe Amato; Fabio Carrara; Claudio Gennaro; Marco Di Benedetto; | arxiv-cs.CV | 2025-03-28 |
| 875 | Opioid Named Entity Recognition (ONER-2025) from Reddit Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Fourth, we propose a real-time monitoring system to processstreaming data from social media, healthcare records, and emergency services toidentify overdose events. |
Muhammad Ahmad; Rita Orji; Fida Ullah; Ildar Batyrshin; Grigori Sidorov; | arxiv-cs.CL | 2025-03-28 |
| 876 | A BERT‐Based Multi‐Embedding Fusion Method Using Review Text for Recommendation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Collaborative filtering is a widely used method in recommender systems research. However, contrary to the assumption that it relies solely on rating data, many contemporary models … |
Haebin Lim; Qinglong Li; Sigeon Yang; Jaekyeong Kim; | Expert Systems | 2025-03-27 |
| 877 | JEEM: Vision-Language Understanding in Four Arabic Dialects Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce JEEM, a benchmark designed to evaluate Vision-Language Models (VLMs) on visual understanding across four Arabic-speaking countries: Jordan, The Emirates, Egypt, and Morocco. |
KARIMA KADAOUI et. al. | arxiv-cs.CL | 2025-03-27 |
| 878 | How Well Can Vison-Language Models Understand Humans’ Intention? An Open-ended Theory of Mind Question Evaluation Benchmark Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose an open-ended question framework to evaluate VLMs’ performance across diverse categories of ToM tasks. |
Ximing Wen; Mallika Mainali; Anik Sen; | arxiv-cs.CV | 2025-03-27 |
| 879 | An Evaluation of LLMs and Google Translate for Translation of Selected Indian Languages Via Sentiment and Semantic Analyses Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: There has been limited study on theassessment of the quality of translations generated by LLMs, including Gemini,GPT, and Google Translate. This study addresses this limitation by usingsemantic and sentiment analysis of selected LLMs for Indian languages,including Sanskrit, Telugu and Hindi. |
Rohitash Chandra; Aryan Chaudhari; Yeshwanth Rayavarapu; | arxiv-cs.CL | 2025-03-27 |
| 880 | Low-Resource Transliteration for Roman-Urdu and Urdu Using Transformer-Based Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a transformer-based approach using the m2m100 multilingual translation model, enhanced with masked language modeling (MLM) pretraining and fine-tuning on both Roman-Urdu-Parl and the domain-diverse Dakshina dataset. |
Umer Butt; Stalin Veranasi; Günter Neumann; | arxiv-cs.CL | 2025-03-27 |
| 881 | Can Large Language Models Predict Associations Among Human Attitudes? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Prior work has shown that large language models (LLMs) can predict human attitudes based on other attitudes, but this work has largely focused on predictions from highly similar and interrelated attitudes. |
Ana Ma; Derek Powell; | arxiv-cs.CL | 2025-03-26 |
| 882 | Iterative Prompting with Persuasion Skills in Jailbreaking Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Large language models (LLMs) are designed to align with human values in their responses. |
Shih-Wen Ke; Guan-Yu Lai; Guo-Lin Fang; Hsi-Yuan Kao; | arxiv-cs.CL | 2025-03-26 |
| 883 | Advancements in Natural Language Processing: Exploring Transformer-Based Architectures for Text Understanding Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work underscores the pivotal role of transformers in modern NLP and suggests future directions, including efficiency optimization and multimodal integration, to further advance language-based AI systems. |
Tianhao Wu; Yu Wang; Ngoc Quach; | arxiv-cs.CL | 2025-03-26 |
| 884 | BiblioPage: A Dataset of Scanned Title Pages for Bibliographic Metadata Extraction Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Despite advances in machine learning, the absence of dedicated datasets for metadata extraction hinders automation. To address this gap, we introduce BiblioPage, a dataset of scanned title pages annotated with structured bibliographic metadata. |
Jan Kohút; Martin Dočekal; Michal Hradiš; Marek Vaško; | arxiv-cs.CV | 2025-03-25 |
| 885 | S-Transformer: A New Deep Learning Model Enhanced By Sequential Transformer Encoders for Drought Forecasting Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Droughts are prolonged periods of rainfall deficit, the frequency of which has increased due to global warming, causing severe impacts on water resources, agriculture, ecosystems, … |
ALI DANANDEH MEHR et. al. | Earth Sci. Informatics | 2025-03-25 |
| 886 | SCI-IDEA: Context-Aware Scientific Ideation Using Token and Sentence Embeddings Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce SCI-IDEA, a framework that uses LLM prompting strategies and Aha Moment detection for iterative idea refinement. |
FARHANA KEYA et. al. | arxiv-cs.CL | 2025-03-24 |
| 887 | Self-Reported Confidence of Large Language Models in Gastroenterology: Analysis of Commercial, Open-Source, and Quantized Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study evaluated self-reported response certainty across several large language models (GPT, Claude, Llama, Phi, Mistral, Gemini, Gemma, and Qwen) using 300 gastroenterology board-style questions. |
NARIMAN NADERI et. al. | arxiv-cs.CL | 2025-03-24 |
| 888 | Expanding Automated Accessibility Evaluations: Leveraging Large Language Models for Heading-Related Barriers Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Ensuring digital resources are accessible to all users, including those with disabilities, is critical in today’s digital landscape. The growing volume of online content has … |
Carlos Duarte; Miguel Costa; Letícia Seixas Pereira; João Guerreiro; | Companion Proceedings of the 30th International Conference … | 2025-03-24 |
| 889 | Context-Aware Semantic Segmentation: Enhancing Pixel-Level Understanding with Large Language Models for Advanced Vision Applications Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Current models, such as CNN and Transformer-based architectures, excel at identifying pixel-level features but fail to distinguish semantically similar objects (e.g., doctor vs. nurse in a hospital scene) or understand complex contextual scenarios (e.g., differentiating a running child from a regular pedestrian in autonomous driving). To address these limitations, we proposed a novel Context-Aware Semantic Segmentation framework that integrates Large Language Models (LLMs) with state-of-the-art vision backbones. |
Ben Rahman; | arxiv-cs.CV | 2025-03-24 |
| 890 | How to Capture and Study Conversations Between Research Participants and ChatGPT: GPT for Researchers (g4r.org) Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Despite the widespread use of LLMs, researchers lack standardized tools for systematically studying people’s interactions with LLMs. To address this issue, we introduce GPT for Researchers (G4R), or g4r.org, a free website that researchers can use to easily create and integrate a GPT Interface into their studies. |
Jin Kim; | arxiv-cs.HC | 2025-03-23 |
| 891 | GeoBenchX: Benchmarking LLMs in Agent Solving Multistep Geospatial Tasks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We develop a LLM-as-Judge evaluation framework tocompare agent solutions against reference solutions. |
Varvara Krechetova; Denis Kochedykov; | arxiv-cs.CL | 2025-03-23 |
| 892 | Investigating Recent Large Language Models for Vietnamese Machine Reading Comprehension Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we fine-tune and evaluate two state-of-the-art LLMs: Llama 3 (8B parameters) and Gemma (7B parameters), on ViMMRC, a Vietnamese MRC dataset. |
Anh Duc Nguyen; Hieu Minh Phi; Anh Viet Ngo; Long Hai Trieu; Thai Phuong Nguyen; | arxiv-cs.CL | 2025-03-23 |
| 893 | LakotaBERT: A Transformer-based Model for Low Resource Lakota Language Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces LakotaBERT, the first large language model (LLM) tailored for Lakota, aiming to support language revitalization efforts. |
Kanishka Parankusham; Rodrigue Rizk; KC Santosh; | arxiv-cs.CL | 2025-03-23 |
| 894 | Fine-Tuned RoBERTa Model for Bug Detection in Mobile Games: A Comprehensive Approach Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In the current digital era, the Google Play Store and the App Store are major platforms for the distribution of mobile applications and games. Billions of users regularly download … |
M. USMAN et. al. | Comput. | 2025-03-21 |
| 895 | Assessing The Reliability and Validity of GPT-4 in Annotating Emotion Appraisal Ratings Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Appraisal theories suggest that emotions arise from subjective evaluations of events, referred to as appraisals. |
Deniss Ruder; Andero Uusberg; Kairit Sirts; | arxiv-cs.CL | 2025-03-21 |
| 896 | Can Zero-Shot Commercial APIs Deliver Regulatory-Grade Clinical Text DeIdentification? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We evaluate the performance of four leading solutions for de-identification of unstructured medical text – Azure Health Data Services, AWS Comprehend Medical, OpenAI GPT-4o, and John Snow Labs – on a ground truth dataset of 48 clinical documents annotated by medical experts. |
Veysel Kocaman; Muhammed Santas; Yigit Gul; Mehmet Butgul; David Talby; | arxiv-cs.CL | 2025-03-21 |
| 897 | Beyond Negation Detection: Comprehensive Assertion Detection Models for Clinical NLP Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To address this gap, we developed state-of-the-art assertion detection models, including fine-tuned LLMs, transformer-based classifiers, few-shot classifiers, and deep learning (DL) approaches. We evaluated these models against cloud-based commercial API solutions, the legacy rule-based NegEx approach, and GPT-4o. |
VEYSEL KOCAMAN et. al. | arxiv-cs.CL | 2025-03-21 |
| 898 | Design and Implementation of An FPGA-Based Tiled Matrix Multiplication Accelerator for Transformer Self-Attention on The Xilinx KV260 SoM Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: Transformer-based large language models (LLMs) rely heavily on intensive matrix multiplications for attention and feed-forward layers, with the Q, K, and V linear projections in … |
Richie Li; Sicheng Chen; | ArXiv | 2025-03-20 |
| 899 | InhibiDistilbert: Knowledge Distillation for A ReLU and Addition-based Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This shift offers potential computational and energy savings while maintaining model effectiveness. We propose further adjustments to improve the inhibitor mechanism’s training efficiency and evaluate its performance on the DistilBERT architecture. |
Tony Zhang; Rickard Brännvall; | arxiv-cs.CL | 2025-03-20 |
| 900 | Design and Implementation of An FPGA-Based Hardware Accelerator for Transformer Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Transformer-based large language models (LLMs) rely heavily on intensive matrix multiplications for attention and feed-forward layers, with the Q, K, and V linear projections in the Multi-Head Self-Attention (MHA) module constituting a decisive performance bottleneck. In this work, we introduce a highly optimized tiled matrix multiplication accelerator on a resource-constrained Xilinx KV260 FPGA that not only addresses this challenge but sets a new standard for efficiency and performance. |
Richie Li; Sicheng Chen; | arxiv-cs.AR | 2025-03-20 |
| 901 | Mapping The Landscape of Generative Artificial Intelligence in Learning Analytics: A Systematic Literature Review Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Generative artificial intelligence (GenAI) has opened new possibilities for designing learning analytics (LA) tools, gaining new insights about student learning processes and … |
Kamila Misiejuk; Sonsoles López-Pernas; Rogers Kaliisa; M. Saqr; | J. Learn. Anal. | 2025-03-20 |
| 902 | ATTENTION2D: Communication Efficient Distributed Self-Attention Mechanism Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce ATTENTION2D, a novel approach that exploitsparallelism along two dimensions – query and key/value – of the self-attentionoperation. |
Venmugil Elango; | arxiv-cs.LG | 2025-03-19 |
| 903 | How Well Can AI Build SD Models? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To reduce uncertainty about how well AI can build SD models, we introduce two metrics for evaluation of AI-generated causal maps: technical correctness (causal translation) and adherence to instructions (conformance). |
WILLIAM SCHOENBERG et. al. | arxiv-cs.AI | 2025-03-19 |
| 904 | Understanding The Generalization of In-Context Learning in Transformers: An Empirical Study Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present a systematic investigation of transformers’ generalization capability with ICL relative to training data coverage by defining a task-centric framework along three dimensions: inter-problem, intra-problem, and intra-task generalization. |
XINGXUAN ZHANG et. al. | arxiv-cs.LG | 2025-03-19 |
| 905 | Assessing Large Language Models for Automated Feedback Generation in Learning Programming Problem Solving Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We assessed the models’ capacity to provide accurate and insightful feedback, particularly in identifying reasoning mistakes. |
Priscylla Silva; Evandro Costa; | arxiv-cs.SE | 2025-03-18 |
| 906 | Multilingual User Perceptions Analysis from Twitter Using Zero Shot Learning for Border Control Technologies Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Online social networks such as Twitter, Facebook, Instagram, and Reddit have transformed communications by enabling users to share their opinions and perceptions. The vast amount … |
Sarang Shaikh; Sule YAYILGAN YILDIRIM; Mohamed Abomhara; Erjon Zoto; | Soc. Netw. Anal. Min. | 2025-03-18 |
| 907 | ExACT: Teaching AI Agents to Explore with Reflective-MCTS and Exploratory Learning IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, even state-of-the-art vision-language models (VLMs), such as GPT-4o, still fall short of human-level performance, particularly in intricate web environments and long-horizon planning tasks. To address these limitations, we introduce Reflective Monte Carlo Tree Search (R-MCTS), a novel test-time algorithm designed to enhance the ability of AI agents, e.g., powered by GPT-4o, to explore decision space on the fly. |
XIAO YU et. al. | iclr | 2025-03-17 |
| 908 | Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Scaling up autoregressive models in vision has not proven as beneficial as in large language models. In this work, we investigate this scaling problem in the context of text-to-image generation, focusing on two critical factors: whether models use discrete or continuous tokens, and whether tokens are generated in a random or fixed raster order using BERT- or GPT-like transformer architectures. |
LIJIE FAN et. al. | iclr | 2025-03-17 |
| 909 | VibeCheck: Discover and Quantify Qualitative Differences in Large Language Models IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce $\textbf{VibeCheck}$, a system for automatically comparing a pair of LLMs by discovering identifying traits of a model (vibes) that are well-defined, differentiating, and user-aligned. |
Lisa Dunlap; Krishna Mandal; Trevor Darrell; Jacob Steinhardt; Joseph E. Gonzalez; | iclr | 2025-03-17 |
| 910 | Forgetting Transformer: Softmax Attention with A Forget Gate IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We show that FoX outperforms the Transformer on long-context language modeling, length extrapolation, and short-context downstream tasks, while performing on par with the Transformer on long-context downstream tasks. |
Zhixuan Lin; Evgenii Nikishin; Xu He; Aaron Courville; | iclr | 2025-03-17 |
| 911 | ACE: All-round Creator and Editor Following Instructions Via Diffusion Transformer IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose ACE, an All-round Creator and Editor, which achieves comparable performance compared to those expert models in a wide range of visual generation tasks. |
ZHEN HAN et. al. | iclr | 2025-03-17 |
| 912 | Dynamic Diffusion Transformer IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Specifically, we introduce a Timestep-wise Dynamic Width (TDW) approach that adapts model width conditioned on the generation timesteps. |
WANGBO ZHAO et. al. | iclr | 2025-03-17 |
| 913 | Lightweight Neural App Control Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces a novel mobile phone control architecture, Lightweight Multi-modal App Control (LiMAC), for efficient interactions and control across various Android apps. |
FILIPPOS CHRISTIANOS et. al. | iclr | 2025-03-17 |
| 914 | KiVA: Kid-inspired Visual Analogies for Testing Large Multimodal Models IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: While benchmarks exist for testing visual reasoning in LMMs, they require advanced skills and omit basic visual analogies that even young children can make. Inspired by developmental psychology, we propose a new benchmark of 4,300 visual transformations of everyday objects to test LMMs on visual analogical reasoning and compare them to children (ages three to five) and to adults. |
EUNICE YIU et. al. | iclr | 2025-03-17 |
| 915 | Ask, and It Shall Be Given: On The Turing Completeness of Prompting Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Here, we present the first theoretical study on the LLM prompting paradigm to the best of our knowledge. In this work, we show that prompting is in fact Turing-complete: there exists a finite-size Transformer such that for any computable function, there exists a corresponding prompt following which the Transformer computes the function. |
Ruizhong Qiu; Zhe Xu; Wenxuan Bao; Hanghang Tong; | iclr | 2025-03-17 |
| 916 | Improving Language Model Distillation Through Hidden State Matching Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present an alternative technique using Centered Kernel Alignment (CKA) to match hidden states of different dimensionality, allowing for smaller students and higher compression ratios. |
Sayantan Dasgupta; Trevor Cohn; | iclr | 2025-03-17 |
| 917 | Token Statistics Transformer: Linear-Time Attention Via Variational Rate Reduction Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose a novel transformer attention operator whose computational complexity scales linearly with the number of tokens. |
ZIYANG WU et. al. | iclr | 2025-03-17 |
| 918 | Competing Large Language Models in Multi-Agent Gaming Environments IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce GAMA($\gamma$)-Bench, a new framework for evaluating LLMs’ Gaming Ability in Multi-Agent environments. |
JEN-TSE HUANG et. al. | iclr | 2025-03-17 |
| 919 | API Pack: A Massive Multi-Programming Language Dataset for API Call Generation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce API Pack, a massive multi-programming language dataset containing over one million instruction-API calls for improving the API call generation capabilities of large language models. |
Zhen Guo; Adriana Meza Soria; Wei Sun; Yikang Shen; Rameswar Panda; | iclr | 2025-03-17 |
| 920 | Feature Extraction and Analysis for GPT-Generated Text Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present a comprehensive study of feature extraction and analysis for differentiating between human-written and GPT-generated text. |
A. Selvioğlu; V. Adanova; M. Atagoziev; | arxiv-cs.CL | 2025-03-17 |
| 921 | A Spark of Vision-Language Intelligence: 2-Dimensional Autoregressive Transformer for Efficient Finegrained Image Generation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This work tackles the information loss bottleneck of vector-quantization (VQ) autoregressive image generation by introducing a novel model architecture called the 2-Dimensional Autoregression (DnD) Transformer. |
LIANG CHEN et. al. | iclr | 2025-03-17 |
| 922 | Motion-Agent: A Conversational Framework for Human Motion Generation with LLMs IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: While previous approaches to 3D human motion generation have achieved notable success, they often rely on extensive training and are limited to specific tasks. To address these challenges, we introduce **Motion-Agent**, an efficient conversational framework designed for general human motion generation, editing, and understanding. |
QI WU et. al. | iclr | 2025-03-17 |
| 923 | Mixture-of-Agents Enhances Large Language Model Capabilities IF:5 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: With the growing number of LLMs, how to harness the collective expertise of multiple LLMs is an exciting open direction. Toward this goal, we propose a new approach that leverages the collective strengths of multiple LLMs through a Mixture-of-Agents (MoA) methodology. |
Junlin Wang; Jue WANG; Ben Athiwaratkun; Ce Zhang; James Zou; | iclr | 2025-03-17 |
| 924 | Timer-XL: Long-Context Transformers for Unified Time Series Forecasting IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present Timer-XL, a causal Transformer for unified time series forecasting. |
Yong Liu; Guo Qin; Xiangdong Huang; Jianmin Wang; Mingsheng Long; | iclr | 2025-03-17 |
| 925 | Qualitative Coding with GPT-4: Where It Works Better Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This study explores the potential of the large language model GPT-4 as an automated tool for qualitative data analysis by educational researchers, exploring which techniques are … |
XINER LIU et. al. | J. Learn. Anal. | 2025-03-17 |
| 926 | DreamBench++: A Human-Aligned Benchmark for Personalized Image Generation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we present DreamBench++, a human-aligned benchmark that advanced multimodal GPT models automate.Further, we construct a comprehensive dataset comprising diverse images and prompts. |
YUANG PENG et. al. | iclr | 2025-03-17 |
| 927 | LLM & HPC:Benchmarking DeepSeek’s Performance in High-Performance Computing Tasks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Large Language Models (LLMs), such as GPT-4 and DeepSeek, have been applied to a wide range of domains in software engineering. |
Noujoud Nader; Patrick Diehl; Steve Brandt; Hartmut Kaiser; | arxiv-cs.DC | 2025-03-15 |
| 928 | BriLLM: Brain-inspired Large Language Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce BriLLM, a brain-inspired large language model that fundamentallyredefines the foundations of machine learning through its implementation ofSignal Fully-connected flowing (SiFu) learning. |
Hai Zhao; Hongqiu Wu; Dongjie Yang; Anni Zou; Jiale Hong; | arxiv-cs.CL | 2025-03-14 |
| 929 | Text Compression for Efficient Language Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To this end, we propose the Generative Pretrained Thoughtformer (GPTHF), a hierarchical transformer language model capable of text generation by compressing text into sentence embeddings and employing a sentence attention mechanism. |
David Gu; Peter Belcak; Roger Wattenhofer; | arxiv-cs.CL | 2025-03-14 |
| 930 | Exploring The Potential of Large Multimodal Models As Effective Alternatives for Pronunciation Assessment Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Large Multimodal Models (LMMs) have demonstrated exceptional performance across a wide range of domains. |
KE WANG et. al. | arxiv-cs.SD | 2025-03-14 |
| 931 | Bridging The LLM Accessibility Divide? Performance, Fairness, and Cost of Closed Versus Open LLMs for Automated Essay Scoring Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we perform a rigorous comparative analysis of nine leading LLMs, spanning closed, open, and open-source LLM ecosystems, across text assessment and generation tasks related to automated essay scoring. |
Kezia Oketch; John P. Lalor; Yi Yang; Ahmed Abbasi; | arxiv-cs.CL | 2025-03-14 |
| 932 | Prompt Sentiment: The Catalyst for LLM Change Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study systematically examines how sentiment variations in prompts affect LLM-generated outputs in terms of coherence, factuality, and bias. |
Vishal Gandhi; Sagar Gandhi; | arxiv-cs.CL | 2025-03-14 |
| 933 | Prompt Alchemy: Automatic Prompt Refinement for Enhancing Code Generation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper introduces Prochemy, an innovative method for automatically refining prompts to boost code generation. |
SIXIANG YE et. al. | arxiv-cs.SE | 2025-03-14 |
| 934 | ARLED: Leveraging LED-based ARMAN Model for Abstractive Summarization of Persian Long Documents Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The paper provides a comprehensive overview of related work, discusses the methodology, presents the experimental results, and concludes with future research directions. |
Samira Zangooei; Amirhossein Darmani; Hossein Farahmand Nezhad; Laya Mahmoudi; | arxiv-cs.CL | 2025-03-13 |
| 935 | Tempest: Autonomous Multi-Turn Jailbreaking of Large Language Models with Tree Search Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce Tempest, a multi-turn adversarial framework that models the gradual erosion of Large Language Model (LLM) safety through a tree search perspective. |
Andy Zhou; Ron Arel; | arxiv-cs.AI | 2025-03-13 |
| 936 | 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 Highlight: This insight motivates our approach that refines semantic clarity by encoding explicit semantic details within local regions, thus ensuring interoperability and capturing finer-grained features, and by concentrating modifications on semantically rich areas rather than applying them uniformly. To achieve this, we propose a simple yet highly effective solution: at each optimization step, the adversarial image is cropped randomly by a controlled aspect ratio and scale, resized, and then aligned with the target image in the embedding space. |
Zhaoyi Li; Xiaohan Zhao; Dong-Dong Wu; Jiacheng Cui; Zhiqiang Shen; | arxiv-cs.CV | 2025-03-13 |
| 937 | Cognitive-Mental-LLM: Evaluating Reasoning in Large Language Models for Mental Health Prediction Via Online Text Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Large Language Models (LLMs) have demonstrated potential in predicting mental health outcomes from online text, yet traditional classification methods often lack interpretability and robustness. |
Avinash Patil; Amardeep Kour Gedhu; | arxiv-cs.CL | 2025-03-13 |
| 938 | It Is Too Many Options: Pitfalls of Multiple-Choice Questions in Generative AI and Medical Education Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We hypothesized that LLM performance on medical MCQs may in part be illusory and driven by factors beyond medical content knowledge and reasoning capabilities. |
SHRUTIKA SINGH et. al. | arxiv-cs.CL | 2025-03-13 |
| 939 | Towards Algorithmic Framing Analysis: Expanding The Scope By Using LLMs Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Framing analysis, an extensively used, multi-disciplinary social science research method, requires substantial manpower and time to code and uncover human-level understanding of … |
Xianwen Kuang; Jun Liu; Haiyang Zhang; Simon Schweighofer; | J. Big Data | 2025-03-13 |
| 940 | AI-Augmented Advising: A Comparative Study of GPT-4 and Advisor-based Major Recommendations Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Choosing an undergraduate major is an important decision that impacts academic and career outcomes. In this work, we investigate augmenting personalized human advising for major … |
Kasra Lekan; Z. Pardos; | J. Learn. Anal. | 2025-03-13 |
| 941 | Minimal Time Series Transformer Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This work introduces minimal adaptations to make the original transformer architecture suitable for continuous value time series data. |
Joni-Kristian Kämäräinen; | arxiv-cs.LG | 2025-03-12 |
| 942 | Who Are You Behind The Screen? Implicit MBTI and Gender Detection Using Artificial Intelligence Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study emphasizes practical issues in balancing accuracy and data coverage as Transformer-based models show their efficiency in implicit personality and gender prediction tasks from conversational texts. |
Kourosh Shahnazari; Seyed Moein Ayyoubzadeh; | arxiv-cs.CL | 2025-03-12 |
| 943 | Unmask It! AI-Generated Product Review Detection in Dravidian Languages Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Reviews serve as the primary source of information about products and services. |
Somsubhra De; Advait Vats; | arxiv-cs.CL | 2025-03-12 |
| 944 | An Evaluation of LLMs for Detecting Harmful Computing Terms Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Each model was presented with a standardized prompt to identify harmful and non-inclusive language across 64 terms. |
Joshua Jacas; Hana Winchester; Alicia Boyd; Brittany Johnson; | arxiv-cs.CL | 2025-03-12 |
| 945 | Enhancing Large Language Models for Hardware Verification: A Novel SystemVerilog Assertion Dataset Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, proprietary SOTA models like GPT-4o often generate inaccurate assertions and require expensive licenses, while smaller open-source LLMs need fine-tuning to manage HDL code complexities. To address these issues, we introduce **VERT**, an open-source dataset designed to enhance SystemVerilog assertion generation using LLMs. |
ANAND MENON et. al. | arxiv-cs.LG | 2025-03-11 |
| 946 | A Grey-box Text Attack Framework Using Explainable AI Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We proposed a simple yet effective Grey-box cum Black-box approach that does not require the knowledge of the model while using a set of surrogate Transformer/BERT models to perform the attack using Explainable AI techniques. |
Esther Chiramal; Kelvin Soh Boon Kai; | arxiv-cs.CL | 2025-03-11 |
| 947 | Adapting Large Language Models for Parameter-Efficient Log Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To have an in-depth exploration of the potential of LLM-driven LAD, we present a comprehensive investigation of leveraging two of the most popular PEFTs — Low-Rank Adaptation (LoRA) and Representation Fine-tuning (ReFT) — to tap into three prominent LLMs of varying size, including RoBERTa, GPT-2, and Llama-3, for parameter-efficient LAD. Comprehensive experiments on four public log datasets are performed to reveal important insights into effective LLM-driven LAD in several key perspectives, including the efficacy of these PEFT-based LLM-driven LAD methods, their stability, sample efficiency, robustness w.r.t. unstable logs, and cross-dataset generalization. |
Ying Fu Lim; Jiawen Zhu; Guansong Pang; | arxiv-cs.LG | 2025-03-11 |
| 948 | Analyzing The Language of Rejection: A Study of User Flagging Responses to Hate Speech on Reddit Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Introduction. Online hate speech poses significant threats to individuals and society, exacerbating psychological harm, discrimination, and potential real-world violence. While … |
Sharon Lisseth Perez; Xiaoying Song; Lingzi Hong; | Inf. Res. | 2025-03-11 |
| 949 | From Idea to Implementation: Evaluating The Influence of Large Language Models in Software Development — An Opinion Paper Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, opinions from 11 experts regarding their experience with LLMs for software development have been gathered and analysed to draw insights that can guide successful and responsible integration. |
SARGAM YADAV et. al. | arxiv-cs.AI | 2025-03-10 |
| 950 | Enhancing Sentiment Analysis Through Multimodal Fusion: A BERT-DINOv2 Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes a novel multimodal sentiment analysis architecture that integrates text and image data to provide a more comprehensive understanding of sentiments. |
TAOXU ZHAO et. al. | arxiv-cs.CV | 2025-03-10 |
| 951 | Identifying Non-Replicable Social Science Studies with Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we investigate whether LLMs can be used to indicate if a study in the behavioural social sciences is replicable. |
Denitsa Saynova; Kajsa Hansson; Bastiaan Bruinsma; Annika Fredén; Moa Johansson; | arxiv-cs.CL | 2025-03-10 |
| 952 | Exploring Multimodal Perception in Large Language Models Through Perceptual Strength Ratings Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study investigated the multimodal perception of large language models (LLMs), focusing on their ability to capture human-like perceptual strength ratings across sensory modalities. |
Jonghyun Lee; Dojun Park; Jiwoo Lee; Hoekeon Choi; Sung-Eun Lee; | arxiv-cs.CL | 2025-03-10 |
| 953 | GPT-PPG: A GPT-based Foundation Model for Photoplethysmography Signals Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study introduces a novel application of a Generative Pre-trained Transformer (GPT) model tailored for photoplethysmography (PPG) signals, serving as a foundation model for various downstream tasks. |
ZHAOLIANG CHEN et. al. | arxiv-cs.LG | 2025-03-10 |
| 954 | SKG-LLM: Developing A Mathematical Model for Stroke Knowledge Graph Construction Using Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The purpose of this study is to introduce SKG-LLM. |
Ali Sarabadani; Kheirolah Rahsepar Fard; Hamid Dalvand; | arxiv-cs.AI | 2025-03-09 |
| 955 | A LongFormer-Based Framework for Accurate and Efficient Medical Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes a medical text summarization method based on LongFormer, aimed at addressing the challenges faced by existing models when processing long medical texts. |
DAN SUN et. al. | arxiv-cs.CL | 2025-03-09 |
| 956 | Seeing Delta Parameters As JPEG Images: Data-Free Delta Compression with Discrete Cosine Transform Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, existing methods usually face problems including data accessibility and training requirements. To tackle this issue, we introduce Delta-DCT, the first data-free delta compression method inspired by classic JPEG image compression, leveraging the Discrete Cosine Transform (DCT). |
CHENYU HUANG et. al. | arxiv-cs.CV | 2025-03-09 |
| 957 | Multimodal Emotion Recognition and Sentiment Analysis in Multi-Party Conversation Contexts Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Emotion recognition and sentiment analysis are pivotal tasks in speech and language processing, particularly in real-world scenarios involving multi-party, conversational data. This paper presents a multimodal approach to tackle these challenges on a well-known dataset. |
AREF FARHADIPOUR et. al. | arxiv-cs.CV | 2025-03-09 |
| 958 | Effectiveness of Zero-shot-CoT in Japanese Prompts Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We compare the effectiveness of zero-shot Chain-of-Thought (CoT) prompting in Japanese and English using ChatGPT-3.5 and 4o-mini. |
Shusuke Takayama; Ian Frank; | arxiv-cs.CL | 2025-03-09 |
| 959 | Evaluating Large Language Models in Code Generation: INFINITE Methodology for Defining The Inference Index Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study introduces a new methodology for an Inference Index (InI), called INFerence INdex In Testing model Effectiveness methodology (INFINITE), aiming to evaluate the performance of Large Language Models (LLMs) in code generation tasks. |
Nicholas Christakis; Dimitris Drikakis; | arxiv-cs.SE | 2025-03-07 |
| 960 | Zero-shot Medical Event Prediction Using A Generative Pre-trained Transformer on Electronic Health Records Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study presents the first comprehensive analysis of zero-shot forecastingwith GPT-based foundational models in EHRs, introducing a novel pipeline thatformulates medical concept prediction as a generative modeling task. |
EKATERINA REDEKOP et. al. | arxiv-cs.LG | 2025-03-07 |
| 961 | FMT:A Multimodal Pneumonia Detection Model Based on Stacking MOE Framework Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, a Flexible Multimodal Transformer (FMT) was proposed, which uses ResNet-50 and BERT for joint representation learning, followed by a dynamic masked attention strategy that simulates clinical modality loss to improve robustness; finally, a sequential mixture of experts (MOE) architecture was used to achieve multi-level decision refinement. |
Jingyu Xu; Yang Wang; | arxiv-cs.CV | 2025-03-07 |
| 962 | MatrixFlow: System-Accelerator Co-design for High-performance Transformer Applications Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Despite their success, their large parameter count and computational demands challenge efficient acceleration. To address these limitations, this paper proposes MatrixFlow, a novel co-designed system-accelerator architecture based on a loosely coupled systolic array including a new software mapping approach for efficient transformer code execution. |
Qunyou Liu; Marina Zapater; David Atienza; | arxiv-cs.AR | 2025-03-07 |
| 963 | Revisiting The Othello World Model Hypothesis Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Specifically, we analyze sequences of Othello board states and train the model to predict the next move based on previous moves. |
Yifei Yuan; Anders Søgaard; | arxiv-cs.CL | 2025-03-06 |
| 964 | A Dataset for Analysing News Framing in Chinese Media Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study introduces the first Chinese News Framing dataset, to be used as either a stand-alone dataset or a supplementary resource to the SemEval-2023 task 3 dataset. |
Owen Cook; Yida Mu; Xinye Yang; Xingyi Song; Kalina Bontcheva; | arxiv-cs.CL | 2025-03-06 |
| 965 | BPQA Dataset: Evaluating How Well Language Models Leverage Blood Pressures to Answer Biomedical Questions Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: It is an important component of biomedical data, which can be used to train transformer-based language models (LMs) for improving healthcare delivery. |
CHI HANG et. al. | arxiv-cs.CL | 2025-03-06 |
| 966 | Biases in Large Language Model-Elicited Text: A Case Study in Natural Language Inference Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We train hypothesis-only classifiers to determine whether LLM-elicited NLI datasets contain annotation artifacts. |
Grace Proebsting; Adam Poliak; | arxiv-cs.CL | 2025-03-06 |
| 967 | HILGEN: Hierarchically-Informed Data Generation for Biomedical NER Using Knowledgebases and Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present HILGEN, a Hierarchically-Informed Data Generation approach that combines domain knowledge from the Unified Medical Language System (UMLS) with synthetic data generated by large language models (LLMs), specifically GPT-3.5. |
YAO GE et. al. | arxiv-cs.CL | 2025-03-06 |
| 968 | Unpacking Sarcasm: A Contextual and Transformer-Based Approach for Improved Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Sarcasm detection is a crucial task in natural language processing (NLP), particularly in sentiment analysis and opinion mining, where sarcasm can distort sentiment … |
Parul Dubey; Pushkar Dubey; P. Bokoro; | Comput. | 2025-03-06 |
| 969 | Benchmarking Reasoning Robustness in Large Language Models IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Despite the recent success of large language models (LLMs) in reasoning such as DeepSeek, we for the first time identify a key dilemma in reasoning robustness and generalization: significant performance degradation on novel or incomplete data, suggesting a reliance on memorized patterns rather than systematic reasoning. Our closer examination reveals four key unique limitations underlying this issue:(1) Positional bias–models favor earlier queries in multi-query inputs but answering the wrong one in the latter (e.g., GPT-4o’s accuracy drops from 75.8 percent to 72.8 percent); (2) Instruction sensitivity–performance declines by 5.0 to 7.5 percent in the Qwen2.5 Series and by 5.0 percent in DeepSeek-V3 with auxiliary guidance; (3) Numerical fragility–value substitution sharply reduces accuracy (e.g., GPT-4o drops from 97.5 percent to 82.5 percent, GPT-o1-mini drops from 97.5 percent to 92.5 percent); and (4) Memory dependence–models resort to guesswork when missing critical data. |
TONG YU et. al. | arxiv-cs.AI | 2025-03-06 |
| 970 | Scaling Crowdsourced Election Monitoring: Construction and Evaluation of Classification Models for Multilingual and Cross-Domain Classification Settings Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we address the challenge of scaling crowdsourced election monitoring by advancing the task of automated classification of crowdsourced election reports to multilingual and cross-domain classification settings. |
Jabez Magomere; Scott Hale; | arxiv-cs.CL | 2025-03-05 |
| 971 | DTU-Net: A Multi-Scale Dilated Transformer Network for Nonlinear Hyperspectral Unmixing Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Additionally, current Transformer-based unmixing networks rely on the linear mixing model, which lacks the flexibility to accommodate scenarios where nonlinear effects are significant. To address these limitations, we propose a multi-scale Dilated Transformer-based unmixing network for nonlinear HU (DTU-Net). |
ChenTong Wang; Jincheng Gao; Fei Zhu; Abderrahim Halimi; Cédric Richard; | arxiv-cs.CV | 2025-03-05 |
| 972 | Sarcasm Detection As A Catalyst: Improving Stance Detection with Cross-Target Capabilities Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study represents the first exploration of sarcasm detection as an intermediate transfer-learning task within the context of SD while also leveraging the concatenation of BERT or RoBERTa with other deep-learning techniques. The proposed approach establishes a foundational baseline for future research in this domain. |
Gibson Nkhata Shi Yin Hong; Susan Gauch; | arxiv-cs.CL | 2025-03-05 |
| 973 | BatchGEMBA: Token-Efficient Machine Translation Evaluation with Batched Prompting and Prompt Compression Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we introduce BatchGEMBA-MQM, a framework that integrates batched prompting with the GEMBA-MQM metric for machine translation evaluation. |
Daniil Larionov; Steffen Eger; | arxiv-cs.CL | 2025-03-04 |
| 974 | An Enhanced Aspect-Based Sentiment Analysis Model Based on RoBERTa For Text Sentiment Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View |
Amit Chauhan; Aman Sharma; R. Mohana; | Informatica (Slovenia) | 2025-03-04 |
| 975 | Weak-to-Strong Generalization Even in Random Feature Networks, Provably Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We consider student and teacherthat are random feature models, described by two-layer networks with a randomand fixed bottom layer and a trained top layer. |
MARKO MEDVEDEV et. al. | arxiv-cs.LG | 2025-03-04 |
| 976 | Intermediate-Task Transfer Learning: Leveraging Sarcasm Detection for Stance Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Our experiments also revealed that the success of the transfer-learning framework is contingent upon the correlation of lexical attributes between the intermediate task and the target task. This study represents the first exploration of sarcasm detection as an intermediate transfer-learning task in the context of SD and simultaneously uses the concatenation of BERT or RoBERTa with other deep-learning techniques establishing the proposed approach as a foundational baseline for future research endeavors in this domain. |
Gibson Nkhata; Susan Gauch; | arxiv-cs.CL | 2025-03-04 |
| 977 | Examining The Mental Health Impact of Misinformation on Social Media Using A Hybrid Transformer-Based Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The unchecked spread of false narratives has profound effects on mental health, contributing to increased stress, anxiety, and misinformation-driven paranoia. This study presents a hybrid transformer-based approach using a RoBERTa-LSTM classifier to detect misinformation, assess its impact on mental health, and classify disorders linked to misinformation exposure. |
SARVESH ARORA et. al. | arxiv-cs.CL | 2025-03-04 |
| 978 | The Effectiveness of Large Language Models in Transforming Unstructured Text to Standardized Formats Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Through comprehensive testing of four models (GPT-4o, GPT-4o-mini, Llama3.1:70b, and Llama3.1:8b), an innovative evaluation approach is introduced that combines traditional metrics (WER, ROUGE-L, TER) with specialized metrics for semantic element identification. |
William Brach; Kristián Košťál; Michal Ries; | arxiv-cs.AI | 2025-03-04 |
| 979 | Comparative Analysis of OpenAI GPT-4o and DeepSeek R1 for Scientific Text Categorization Using Prompt Engineering Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, its performance in scientific text categorization remains unexplored. To address this gap, we introduce a new evaluation method designed specifically for this task. |
ANIRUDDHA MAITI et. al. | arxiv-cs.CL | 2025-03-03 |
| 980 | That’s What RoBERTa Said: Explainable Classification of Peer Feedback Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Peer feedback (PF) is essential for improving student learning outcomes, particularly in Computer-Supported Collaborative Learning (CSCL) settings. When using digital tools for PF … |
KEVIN HUANG et. al. | Proceedings of the 15th International Learning Analytics … | 2025-03-03 |
| 981 | Generating Effective Distractors for Introductory Programming Challenges: LLMs Vs Humans Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: As large language models (LLMs) show great promise in generating a wide spectrum of educational materials, robust yet cost-effective assessment of the quality and effectiveness of … |
MOHAMMAD HASSANY et. al. | Proceedings of the 15th International Learning Analytics … | 2025-03-03 |
| 982 | Forgetting Transformer: Softmax Attention with A Forget Gate IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We show that FoX outperforms the Transformer on long-context language modeling, length extrapolation, and short-context downstream tasks, while performing on par with the Transformer on long-context downstream tasks. |
Zhixuan Lin; Evgenii Nikishin; Xu Owen He; Aaron Courville; | arxiv-cs.LG | 2025-03-03 |
| 983 | EPEE: Towards Efficient and Effective Foundation Models in Biomedicine Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Despite these advancements, the high inference latency and the overthinking issues in model inference impair the efficiency and effectiveness of foundation models, thus limiting their application in real-time clinical settings. To address these challenges, we proposed EPEE (Entropy- and Patience-based Early Exiting), a novel hybrid strategy designed to improve the inference efficiency of foundation models. |
Zaifu Zhan; Shuang Zhou; Huixue Zhou; Zirui Liu; Rui Zhang; | arxiv-cs.AI | 2025-03-03 |
| 984 | Primus: Enforcing Attention Usage for 3D Medical Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we a) analyze current Transformer-based segmentation models and identify critical shortcomings, particularly their over-reliance on convolutional blocks. |
TASSILO WALD et. al. | arxiv-cs.CV | 2025-03-03 |
| 985 | Network Traffic Classification Using Machine Learning, Transformer, and Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study uses various models to address network traffic classification, categorizing traffic into web, browsing, IPSec, backup, and email. |
Ahmad Antari; Yazan Abo-Aisheh; Jehad Shamasneh; Huthaifa I. Ashqar; | arxiv-cs.LG | 2025-03-03 |
| 986 | Cancer Type, Stage and Prognosis Assessment from Pathology Reports Using LLMs Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this project, we leverage state-of-the-art language models, including the GPT family, Mistral models, and the open-source Llama models, to evaluate their performance in comprehensively analyzing pathology reports. |
RACHIT SALUJA et. al. | arxiv-cs.CL | 2025-03-03 |
| 987 | Automatic Short Answer Grading in The LLM Era: Does GPT-4 with Prompt Engineering Beat Traditional Models? Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Assessing short answers in educational settings is challenging due to the need for scalability and accuracy, which led to the field of Automatic Short Answer Grading (ASAG). … |
RAFAEL FERREIRA MELLO et. al. | Proceedings of the 15th International Learning Analytics … | 2025-03-03 |
| 988 | Multi-modal Wound Classification Using Wound Image and Location By Swin Transformer and Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View |
Ramin Mousa; Behnaz Rezaei; Laya Mahmoudi; Jafar Abdollahi; | Expert Syst. Appl. | 2025-03-01 |
| 989 | FefDM-Transformer: Dual-channel Multi-stage Transformer-based Encoding and Fusion Mode for Infrared-visible Images Related Papers Related Patents Related Grants Related Venues Related Experts View |
Junwu Li; Yaomin Wang; Xin Ning; Wenguang He; Weiwei Cai; | Expert Syst. Appl. | 2025-03-01 |
| 990 | BET‐BiLSTM Model: A Robust Solution for Automated Requirements Classification Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Transformer methods have revolutionized software requirements classification by combining advanced natural language processing to accurately understand and categorize … |
Jalil Abbas; Chengsi Zhang; Bin Luo; | Journal of Software: Evolution and Process | 2025-03-01 |
| 991 | Swin-MGNet: Swin Transformer Based Multiview Grouping Network for 3-D Object Recognition Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Recent developments in Swin Transformer have shown its great potential in various computer vision tasks, including image classification, semantic segmentation, and object … |
XIN NING et. al. | IEEE Transactions on Artificial Intelligence | 2025-03-01 |
| 992 | Psychological Counseling Ability of Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we assessed the psychological counseling ability of mainstream LLMs using 1096 psychological counseling skill questions which were selected from the Chinese National Counselor Level 3 Examination, including Knowledge-based, Analytical-based, and Application-based question types. |
Fangyu Peng; Jingxin Nie; | arxiv-cs.LG | 2025-03-01 |
| 993 | LLMs for Product Classification in E-commerce: A Zero-shot Comparative Study of GPT and Claude Models Related Papers Related Patents Related Grants Related Venues Related Experts View |
Konstantinos I. Roumeliotis; Nikolaos D. Tselikas; Dimitrios K. Nasiopoulos; | Nat. Lang. Process. J. | 2025-03-01 |
| 994 | PAISE: PIM-Accelerated Inference Scheduling Engine for Transformer-based LLM Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Transformer-based Large Language Models (LLMs) demand significant computational and memory resources due to the autoregressive token generation in decoder blocks. In particular, … |
HYOJUNG LEE et. al. | 2025 IEEE International Symposium on High Performance … | 2025-03-01 |
| 995 | Exploiting GPT for Synthetic Data Generation: An Empirical Study Related Papers Related Patents Related Grants Related Venues Related Experts View |
Tony Busker; Sunil Choenni; M. Bargh; | Gov. Inf. Q. | 2025-03-01 |
| 996 | BERT-based Model for Vietnamese Fact Verification Dataset Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces an approach to address the challenges of Fact Verification using the Vietnamese dataset by integrating both sentence selection and classification modules into a unified network architecture. |
BAO TRAN et. al. | arxiv-cs.CL | 2025-03-01 |
| 997 | WebFAQ: A Multilingual Collection of Natural Q&A Datasets for Dense Retrieval Related Papers Related Patents Related Grants Related Venues Related Experts View 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 Mitrović; Michael Granitzer; | arxiv-cs.CL | 2025-02-28 |
| 998 | Measuring Determinism in Large Language Models for Software Code Review Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we tested four leading LLMs — GPT-4o mini, GPT-4o, Claude 3.5 Sonnet, and LLaMA 3.2 90B Vision — on 70 Java commits from both private and public repositories. |
Eugene Klishevich; Yegor Denisov-Blanch; Simon Obstbaum; Igor Ciobanu; Michal Kosinski; | arxiv-cs.SE | 2025-02-28 |
| 999 | À La Recherche Du Sens Perdu: Your Favourite LLM Might Have More to Say Than You Can Understand Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We report a peculiar observation that LLMs can assign hidden meanings to sequences that seem visually incomprehensible to humans: for example, a nonsensical phrase consisting of Byzantine musical symbols is recognized by gpt-4o as say abracadabra. |
K. O. T. Erziev; | arxiv-cs.CL | 2025-02-28 |
| 1000 | FuseForm: Multimodal Transformer for Semantic Segmentation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: For semantic segmentation, integrating multimodal data can vastly improve segmentation performance at the cost of increased model complexity. We introduce FuseForm, a multimodal … |
Justin McMillen; Yasin Yilmaz; | 2025 IEEE/CVF Winter Conference on Applications of Computer … | 2025-02-28 |