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 | 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 |
| 2 | 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 |
| 3 | Omni-Router: Sharing Routing Decisions in Sparse Mixture-of-Experts for Speech Recognition Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To increase thecooperation between experts in different layers and encourage greaterspecialization, we use a shared router across different MoE layers. |
Zijin Gu; Tatiana Likhomanenko; Navdeep Jaitly; | arxiv-cs.CL | 2025-07-08 |
| 4 | 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 Ahmad; Yang Liu; | arxiv-cs.CL | 2025-07-08 |
| 5 | 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 |
| 6 | The Fourier Spectral Transformer Networks For Efficient and Generalizable Nonlinear PDEs Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work we propose a unified Fourier Spectral Transformer network thatintegrates the strengths of classical spectral methods and attention basedneural architectures. |
Beibei Li; | arxiv-cs.LG | 2025-07-07 |
| 7 | 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 |
| 8 | 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 |
| 9 | Seamlessly Integrating Tree-Based Positional Embeddings Into Transformer Models for Source Code Representation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Nonetheless, traditional positionalembeddings employed by these models inadequately capture the hierarchicalstructure intrinsic to source code, typically represented as Abstract SyntaxTrees (ASTs). To address this, we propose a novel tree-based positionalembedding approach that explicitly encodes hierarchical relationships derivedfrom ASTs, including node depth and sibling indices. |
Patryk Bartkowiak; Filip Graliński; | arxiv-cs.LG | 2025-07-05 |
| 10 | 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 |
| 11 | 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 |
| 12 | 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 |
| 13 | APRMCTS: Improving LLM-based Automated Program Repair with Iterative Tree Search Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we proposeAPRMCTS, which uses iterative tree search to improve LLM-based APR. |
Haichuan Hu; Congqing He; Hao Zhang; Xiaochen Xie; Quanjun Zhang; | arxiv-cs.SE | 2025-07-02 |
| 14 | 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 |
| 15 | 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 |
| 16 | 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 |
| 17 | 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 |
| 18 | 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 |
| 19 | 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 |
| 20 | 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 |
| 21 | 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 |
| 22 | 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 |
| 23 | 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 |
| 24 | Data Augmentation for Cognitive Behavioral Therapy: Leveraging ERNIE Language Models Using Artificial Intelligence Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Cognitive Behavioral Therapy (CBT) is a proven approach for addressing theirrational thought patterns associated with mental health disorders, but itseffectiveness relies on … |
Bosubabu Sambana; Kondreddygari Archana; Suram Indhra Sena Reddy; Shaik Meethaigar Jameer Basha; Shaik Karishma; | arxiv-cs.AI | 2025-06-29 |
| 25 | 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 |
| 26 | 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 |
| 27 | 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 |
| 28 | 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 |
| 29 | 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 |
| 30 | 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 |
| 31 | 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 |
| 32 | 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 |
| 33 | 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 |
| 34 | 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 |
| 35 | 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 |
| 36 | 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 |
| 37 | 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 |
| 38 | 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 |
| 39 | MAS-GPT: Training LLMs to Build LLM-based Multi-Agent Systems 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 |
| 40 | 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 |
| 41 | AdvMIM: Adversarial Masked Image Modeling for Semi-Supervised Medical Image Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose an adversarial masked image modeling method tofully unleash the potential of transformer for semi-supervised medical imagesegmentation. |
Lei Zhu; Jun Zhou; Rick Siow Mong Goh; Yong Liu; | arxiv-cs.CV | 2025-06-25 |
| 42 | 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 |
| 43 | 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 |
| 44 | 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 |
| 45 | 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 |
| 46 | FlexTok: Resampling Images Into 1D Token Sequences of Flexible Length 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 |
| 47 | 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 |
| 48 | 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 |
| 49 | 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 |
| 50 | 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 |
| 51 | Weak-to-Strong Generalization Even in Random Feature Networks, Provably Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We then show the quantitative limits of weak-to-strong generalization in this model, and in fact in a much broader class of models, for arbitrary teacher and student feature spaces and a broad class of learning rules, including when the student features are pre-trained or otherwise more informative. In particular, we show that in such models the student’s error can only approach zero if the teacher’s error approaches zero, and a strong student cannot “boost” a slightly-better-then-chance teacher to obtain a small error. |
MARKO MEDVEDEV et. al. | icml | 2025-06-25 |
| 52 | 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 |
| 53 | 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 |
| 54 | 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 |
| 55 | 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 |
| 56 | 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 |
| 57 | 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 |
| 58 | 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 |
| 59 | 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 |
| 60 | ShareGPT-4o-Image: Aligning Multimodal Models with GPT-4o-Level Image Generation 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 |
| 61 | 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 |
| 62 | 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 |
| 63 | 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 |
| 64 | TransDreamerV3: Implanting Transformer In DreamerV3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces TransDreamerV3, a reinforcement learning model thatenhances the DreamerV3 architecture by integrating a transformer encoder. |
Shruti Sadanand Dongare; Amun Kharel; Jonathan Samuel; Xiaona Zhou; | arxiv-cs.LG | 2025-06-20 |
| 65 | 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 |
| 66 | 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 |
| 67 | 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 |
| 68 | A Free Probabilistic Framework for Analyzing The Transformer-based Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We outline an operator-theoretic framework for analyzing transformer-basedlanguage models using the tools of free probability theory. |
Swagatam Das; | arxiv-cs.LG | 2025-06-19 |
| 69 | 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 |
| 70 | 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 |
| 71 | 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 |
| 72 | 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 |
| 73 | 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 |
| 74 | Fretting-Transformer: Encoder-Decoder Model for MIDI to Tablature Transcription Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This contribution introduces the Fretting-Transformer, an encoderdecoder model that utilizes a T5 transformer architecture to automate the transcription of MIDI sequences into guitar tablature. |
Anna Hamberger; Sebastian Murgul; Jochen Schmidt; Michael Heizmann; | arxiv-cs.SD | 2025-06-17 |
| 75 | 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 evaluate FullFlat network architectures, which provide uniform high-bandwidth, low-latency connectivity between all nodes, and demonstrate their transformative impact on performance and scalability. |
Jesmin Jahan Tithi; Hanjiang Wu; Avishaii Abuhatzera; Fabrizio Petrini; | arxiv-cs.AR | 2025-06-17 |
| 76 | 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 |
| 77 | 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; | arxiv-cs.CL | 2025-06-16 |
| 78 | A Gravity-informed Spatiotemporal Transformer for Human Activity Intensity Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Although tremendous progress has been made to model dynamic spatiotemporal patterns of human activity, most existing methods, including spatiotemporal graph neural networks (ST-GNNs), overlook physical constraints of spatial interactions and the over-smoothing phenomenon in spatial correlation modeling. To address these limitations, this work proposes a physics-informed deep learning framework, namely Gravity-informed Spatiotemporal Transformer (Gravityformer) by refining transformer attention to integrate the universal law of gravitation and explicitly incorporating constraints from spatial interactions. |
YI WANG et. al. | arxiv-cs.LG | 2025-06-16 |
| 79 | 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 |
| 80 | 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 |
| 81 | 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 |
| 82 | 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 |
| 83 | 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 |
| 84 | 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 |
| 85 | 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 |
| 86 | 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 |
| 87 | 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 |
| 88 | 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 |
| 89 | 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 |
| 90 | 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 |
| 91 | 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 |
| 92 | 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 |
| 93 | 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 |
| 94 | 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 |
| 95 | 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 |
| 96 | Hierarchical Neural Collapse Detection Transformer for Class Incremental Object Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce a novel framework for IOD, called Hier-DETR: Hierarchical Neural Collapse Detection Transformer, ensuring both efficiency and competitive performance by leveraging Neural Collapse for imbalance dataset and Hierarchical relation of classes’ labels. |
DUC THANH PHAM et. al. | arxiv-cs.CV | 2025-06-10 |
| 97 | CALT: A Library for Computer Algebra with Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we introduce Computer Algebra with Transformer (CALT), a user-friendly Python library designed to help non-experts in deep learning train models for symbolic computation tasks. |
Hiroshi Kera; Shun Arakawa; Yuta Sato; | arxiv-cs.LG | 2025-06-10 |
| 98 | 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 |
| 99 | 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 |
| 100 | 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 |
| 101 | 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 |
| 102 | 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 |
| 103 | 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 |
| 104 | Generative Modeling of Networked Time-Series Via Transformer Architectures Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Recent studies have shown the potential of Transformer models to enlarge the size of data by synthesizing new samples, but the synthesized samples don’t improve the models over the real data. To address this issue, we design an efficient transformer-based model as a generative framework to generate time-series data, that can be used to boost the performance of existing and new ML workflows. |
Yusuf Elnady; | arxiv-cs.LG | 2025-06-08 |
| 105 | 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 |
| 106 | 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 |
| 107 | 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 |
| 108 | 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 |
| 109 | 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 |
| 110 | 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 |
| 111 | 3DTopia-XL: Scaling High-quality 3D Asset Generation Via Primitive Diffusion 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 |
| 112 | RLAIF-V: Open-Source AI Feedback Leads to Super GPT-4V Trustworthiness 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 |
| 113 | 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 |
| 114 | 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 |
| 115 | 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 |
| 116 | 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 autoregressive framework 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 |
| 117 | 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 |
| 118 | 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 in understanding and answering questions from complex data structures found in PDF documents by leveraging industrial and open-source tools as part of a pre-processing pipeline. |
Shivani Upadhyay; Messiah Ataey; Shariyar Murtuza; Yifan Nie; Jimmy Lin; | arxiv-cs.IR | 2025-06-05 |
| 119 | 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 |
| 120 | Theoretical Analysis of Positional Encodings in Transformer Models: Impact on Expressiveness and Generalization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a theoretical framework to analyze how various positional encoding methods, including sinusoidal, learned, relative, and bias-based methods like Attention with Linear Biases (ALiBi), impact a transformer’s expressiveness, generalization ability, and extrapolation to longer sequences. |
Yin Li; | arxiv-cs.LG | 2025-06-05 |
| 121 | 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 |
| 122 | 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 |
| 123 | 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 |
| 124 | Analyzing Transformer Models and Knowledge Distillation Approaches for Image Captioning on Edge AI Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this research, we present findings of transformer-based models for image captioning that operate effectively on edge devices. |
Wing Man Casca Kwok; Yip Chiu Tung; Kunal Bhagchandani; | arxiv-cs.CV | 2025-06-04 |
| 125 | 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 |
| 126 | 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 |
| 127 | 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 |
| 128 | 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 extensible data 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 |
| 129 | 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 |
| 130 | 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 |
| 131 | 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 |
| 132 | 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 |
| 133 | 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 |
| 134 | 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 |
| 135 | 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 |
| 136 | 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 |
| 137 | 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 |
| 138 | Model Internal Sleuthing: Finding Lexical Identity and Inflectional Morphology in Modern Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To better understand today’s language models, we investigate how both classical architectures (BERT, DeBERTa, GPT-2)and contemporary large language models (Pythia, OLMo-2, Gemma-2, Qwen2.5, Llama-3.1) represent lexical identity and inflectional morphology. |
Michael Li; Nishant Subramani; | arxiv-cs.CL | 2025-06-02 |
| 139 | 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 |
| 140 | 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, a high-quality Marathi emotion recognition dataset with 11 fine-grained emotion labels. |
Nidhi Kowtal; Raviraj Joshi; | arxiv-cs.CL | 2025-06-01 |
| 141 | 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 |
| 142 | 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; | arxiv-cs.CR | 2025-05-30 |
| 143 | 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 |
| 144 | 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 |
| 145 | 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 |
| 146 | How Much Do Language Models Memorize? 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 |
| 147 | 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 |
| 148 | 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 |
| 149 | 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 |
| 150 | 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 |
| 151 | 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 |
| 152 | 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 |
| 153 | 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 |
| 154 | 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 |
| 155 | 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 |
| 156 | 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 |
| 157 | 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 |
| 158 | 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 |
| 159 | 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 |
| 160 | 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 |
| 161 | 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 |
| 162 | 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 |
| 163 | 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 |
| 164 | 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 reranking agent. |
Le Zhang; Bo Wang; Xipeng Qiu; Siva Reddy; Aishwarya Agrawal; | arxiv-cs.IR | 2025-05-26 |
| 165 | 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 |
| 166 | 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 |
| 167 | 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 |
| 168 | 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 |
| 169 | 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 |
| 170 | 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 |
| 171 | Multi-Scale Probabilistic Generation Theory: A Hierarchical Framework for Interpreting Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce Multi_Scale Probabilistic Generation Theory (MSPGT), a hierarchical framework that factorizes generation into three semantic scales_global context, intermediate structure, and local word choices and aligns each scale with specific layer ranges in Transformer architectures. |
Yukin Zhang; Qi Dong; | arxiv-cs.CL | 2025-05-23 |
| 172 | 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 |
| 173 | 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 |
| 174 | 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 |
| 175 | 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 |
| 176 | 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; | arxiv-cs.LG | 2025-05-22 |
| 177 | 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 |
| 178 | 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 |
| 179 | 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 |
| 180 | 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 |
| 181 | Scaling Diffusion Transformers Efficiently Via $μ$P Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, it remains unclear whether $\mu$P of vanilla Transformers extends to diffusion Transformers, which differ architecturally and objectively. In this work, we generalize standard $\mu$P to diffusion Transformers and validate its effectiveness through large-scale experiments. |
CHENYU ZHENG et. al. | arxiv-cs.LG | 2025-05-21 |
| 182 | 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 |
| 183 | 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 |
| 184 | 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 |
| 185 | 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 |
| 186 | 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 |
| 187 | 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 |
| 188 | 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 |
| 189 | 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 |
| 190 | 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 |
| 191 | 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 |
| 192 | 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 |
| 193 | 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 |
| 194 | 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 |
| 195 | Swin DiT: Diffusion Transformer Using Pseudo Shifted Windows Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In addition, conventional attention mechanisms exhibit low-frequency inertia issues. To address these issues, we propose \textbf{P}seudo \textbf{S}hifted \textbf{W}indow \textbf{A}ttention (PSWA), which fundamentally mitigates global model redundancy. |
JIAFU WU et. al. | arxiv-cs.CV | 2025-05-19 |
| 196 | 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 |
| 197 | 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 |
| 198 | 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 |
| 199 | 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: While existing approaches have achieved notable results in verifying veracity and cross-modal consistency, two key challenges persist: (1) Existing methods often consider only the global image context while neglecting local object-level details, and (2) they fail to incorporate external knowledge and entity relationships for deeper semantic understanding. To address these challenges, we propose a novel multi-modal fake news detection framework that integrates visual, textual, and knowledge-based representations. |
Tuan-Vinh La; Minh-Hieu Nguyen; Minh-Son Dao; | arxiv-cs.CV | 2025-05-18 |
| 200 | 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 |
| 201 | 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 |
| 202 | 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 |
| 203 | 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 |
| 204 | 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 |
| 205 | Are Sparse Autoencoders Useful for Java Function Bug Detection? Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: While Large Language Models (LLMs) have opened new avenues for classification tasks, their complexity and opacity pose challenges for interpretability and deployment. Sparse Autoencoder offer a promising solution to this problem. |
Rui Melo; Claudia Mamede; Andre Catarino; Rui Abreu; Henrique Lopes Cardoso; | arxiv-cs.SE | 2025-05-15 |
| 206 | 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 |
| 207 | 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 |
| 208 | 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 |
| 209 | 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 |
| 210 | HealthBench: Evaluating Large Language Models Towards Improved Human Health 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 |
| 211 | AC-Reason: Towards Theory-Guided Actual Causality Reasoning with Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, existing LLM-based methods lack grounding in formal AC theory, resulting in limited interpretability. Therefore, we propose AC-Reason, a semi-formal reasoning framework that identifies causally relevant events within an AC scenario, infers the values of their formal causal factors (e.g., sufficiency, necessity, and normality), and answers AC queries via a theory-guided algorithm with explanations. |
YANXI ZHANG et. al. | arxiv-cs.CL | 2025-05-13 |
| 212 | 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 |
| 213 | 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 |
| 214 | 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 |
| 215 | 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 |
| 216 | Lost in Transmission: When and Why LLMs Fail to Reason Globally Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We argue that these failures arise due to capacity limits on the accurate flow of information within LLMs. To formalize this issue, we introduce the bounded attention prefix oracle (BAPO) model, a new computational framework that models bandwidth constraints on attention heads, the mechanism for internal communication in LLMs. |
Tobias Schnabel; Kiran Tomlinson; Adith Swaminathan; Jennifer Neville; | arxiv-cs.AI | 2025-05-12 |
| 217 | 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 |
| 218 | 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 |
| 219 | 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 |
| 220 | 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-MOSEI dataset, using transformer-based models with early fusion to integrate text, audio, and visual modalities. |
Jugal Gajjar; Kaustik Ranaware; | arxiv-cs.CL | 2025-05-09 |
| 221 | 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 |
| 222 | 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 |
| 223 | 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 |
| 224 | 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 |
| 225 | 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 |
| 226 | 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 |
| 227 | 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 |
| 228 | SCFormer: Structured Channel-wise Transformer with Cumulative Historical State for Multivariate Time Series Forecasting Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The Transformer model has shown strong performance in multivariate time series forecasting by leveraging channel-wise self-attention. |
Shiwei Guo; Ziang Chen; Yupeng Ma; Yunfei Han; Yi Wang; | arxiv-cs.LG | 2025-05-05 |
| 229 | 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 |
| 230 | Iterative Self-Tuning LLMs for Enhanced Jailbreaking Capabilities Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Current methods for generating these suffixes are computationally expensive and have low Attack Success Rates (ASR), especially against well-aligned models like Llama2 and Llama3. To overcome these limitations, we introduce **ADV-LLM**, an iterative self-tuning process that crafts adversarial LLMs with enhanced jailbreak ability. |
CHUNG-EN SUN et. al. | naacl | 2025-05-04 |
| 231 | 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 |
| 232 | 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 |
| 233 | 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 |
| 234 | 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 |
| 235 | 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 |
| 236 | 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 |
| 237 | 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 |
| 238 | 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 |
| 239 | 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 |
| 240 | 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 |
| 241 | Intra-Layer Recurrence in Transformers for Language Modeling Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we investigate Intra-Layer Recurrence (ILR), a more targeted approach that applies recurrence selectively to individual layers within a single forward pass. |
Anthony Nguyen; Wenjun Lin; | arxiv-cs.CL | 2025-05-03 |
| 242 | 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 |
| 243 | 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 |
| 244 | 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 |
| 245 | 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 |
| 246 | 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 |
| 247 | Paths-over-Graph: Knowledge Graph Empowered Large Language Model Reasoning 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 |
| 248 | 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 |
| 249 | 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 |
| 250 | 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 |
| 251 | 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 |
| 252 | 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 |
| 253 | 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 |
| 254 | 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 |
| 255 | 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 |
| 256 | Cooking Up Creativity: A Cognitively-Inspired Approach for Enhancing LLM Creativity Through Structured Representations Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce a novel approach that couples LLMs with structured representations and cognitively inspired manipulations to generate more creative and diverse ideas. |
Moran Mizrahi; Chen Shani; Gabriel Stanovsky; Dan Jurafsky; Dafna Shahaf; | arxiv-cs.CL | 2025-04-29 |
| 257 | 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 |
| 258 | 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 |
| 259 | Llama-3.1-FoundationAI-SecurityLLM-Base-8B Technical Report 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 |
| 260 | 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 |
| 261 | 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 |
| 262 | 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 |
| 263 | 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 |
| 264 | 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 |
| 265 | 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 |
| 266 | 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 |
| 267 | 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 |
| 268 | 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 |
| 269 | 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 |
| 270 | 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 |
| 271 | 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 |
| 272 | 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 |
| 273 | 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 |
| 274 | 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 |
| 275 | 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 |
| 276 | 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 |
| 277 | 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 |
| 278 | 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 |
| 279 | 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 |
| 280 | 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 |
| 281 | Efficient Pretraining Length Scaling Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present the Parallel Hidden Decoding Transformer (\textit{PHD}-Transformer), a novel framework that enables efficient length scaling during pre-training while maintaining inference efficiency. |
BOHONG WU et. al. | arxiv-cs.CL | 2025-04-21 |
| 282 | 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 |
| 283 | 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 |
| 284 | 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 |
| 285 | Assessing AI-Generated Questions’ Alignment with Cognitive Frameworks in Educational Assessment Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study evaluates the integration of Bloom’s Taxonomy into OneClickQuiz, an Artificial Intelligence (AI) driven plugin for automating Multiple-Choice Question (MCQ) generation in Moodle. |
Antoun Yaacoub; Jérôme Da-Rugna; Zainab Assaghir; | arxiv-cs.AI | 2025-04-19 |
| 286 | 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 |
| 287 | 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 |
| 288 | 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 |
| 289 | Using LLMs for Library Migration Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Such capabilities suggest that LLMs may be suitable for library migration. Therefore, in this paper, we investigate the effectiveness of LLMs for migration between Python libraries. |
Md Mohayeminul Islam; Ajay Kumar Jha; May Mahmoud; Ildar Akhmetov; Sarah Nadi; | arxiv-cs.SE | 2025-04-17 |
| 290 | 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 |
| 291 | 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 |
| 292 | MSRFormer: Hybrid Scale Self-Attention and Local Fast Convolution Transformer for Facial Expression Recognition Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper we presents a MSRFormer model, which combines Hybrid-scale self-attention and local fast convolution to address existing issues. |
Z. -Q. Shen; Y. -Y. Tang; J. -F. Yan; Y. Li; G. -Y. Zhao; | icassp | 2025-04-15 |
| 293 | 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 |
| 294 | 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 |
| 295 | 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 |
| 296 | 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 |
| 297 | 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 |
| 298 | 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 |
| 299 | 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 |
| 300 | 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 |
| 301 | 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 |
| 302 | 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 |
| 303 | GeMIMO: Searching The Cores of X-formers for Time Series Forecasting Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, these models lack interpretability, making it difficult to identify which components play a core role in predictions and which are redundant. To address this limitation, we introduce the GeMIMO method, which utilizes a heuristic algorithm to identify and refine masks. |
Z. Zhang; Y. Wang; S. Tan; Y. Luo; | icassp | 2025-04-15 |
| 304 | 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 |
| 305 | 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 |
| 306 | TSIformer: Multi-Scale Dilation Transformer with Cross-variable and Cross-feature Dependency for Time Series Imputation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes a Transformer-based model called TSIformer for time series imputation. |
H. YANG et. al. | icassp | 2025-04-15 |
| 307 | Disparity-Guided Cross-View Transformer For Stereo Image Super-Resolution Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a Disparity-Guided Cross-View Transformer (DCT) to extract features across dimensions and views, achieving a more comprehensive feature representation. |
B. LI et. al. | icassp | 2025-04-15 |
| 308 | 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 |
| 309 | 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 |
| 310 | 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 |
| 311 | 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 |
| 312 | 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 |
| 313 | 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 |
| 314 | 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 |
| 315 | 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 |
| 316 | 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 |
| 317 | 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 |
| 318 | 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 |
| 319 | 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 |
| 320 | 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 |
| 321 | 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 |
| 322 | 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 |
| 323 | 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 |
| 324 | 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 |
| 325 | 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 |
| 326 | 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 |
| 327 | 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 |
| 328 | VL-Rethinker: Incentivizing Self-Reflection of Vision-Language Models with Reinforcement Learning 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 |
| 329 | 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 |
| 330 | 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 |
| 331 | 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 |
| 332 | DDT: Decoupled Diffusion Transformer Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To minimize performance degradation, we propose a novel statistical dynamic programming approach to identify optimal sharing strategies. |
Shuai Wang; Zhi Tian; Weilin Huang; Limin Wang; | arxiv-cs.CV | 2025-04-08 |
| 333 | 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 |
| 334 | An Empirical Study of GPT-4o Image Generation Capabilities 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 |
| 335 | 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 |
| 336 | 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 |
| 337 | TAGC: Optimizing Gradient Communication in Distributed Transformer Training Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce Transformer-Aware Gradient Compression (TAGC), an optimized gradient compression algorithm designed specifically for transformer-based models. |
Igor Polyakov; Alexey Dukhanov; Egor Spirin; | arxiv-cs.LG | 2025-04-07 |
| 338 | 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 |
| 339 | 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 |
| 340 | 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 |
| 341 | A Benchmark for End-to-End Zero-Shot Biomedical Relation Extraction with LLMs: Experiments with OpenAI Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Methods: We use OpenAI GPT-4-turbo and their reasoning model o1 to conduct end-to-end RE experiments on seven datasets. |
Aviv Brokman; Xuguang Ai; Yuhang Jiang; Shashank Gupta; Ramakanth Kavuluru; | arxiv-cs.CL | 2025-04-05 |
| 342 | 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 |
| 343 | 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 |
| 344 | 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 |
| 345 | 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 |
| 346 | 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 |
| 347 | GPT-ImgEval: A Comprehensive Benchmark for Diagnosing GPT4o in Image Generation 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 |
| 348 | GEOPARD: Geometric Pretraining for Articulation Prediction in 3D Shapes Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present GEOPARD, a transformer-based architecture for predicting articulation from a single static snapshot of a 3D shape. |
PRADYUMN GOYAL et. al. | arxiv-cs.GR | 2025-04-03 |
| 349 | 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 |
| 350 | 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 |
| 351 | 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 |
| 352 | 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 |
| 353 | Enabling Systematic Generalization in Abstract Spatial Reasoning Through Meta-Learning for Compositionality Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this study, we extend the approach of meta-learning for compositionality to the domain of abstract spatial reasoning. |
Philipp Mondorf; Shijia Zhou; Monica Riedler; Barbara Plank; | arxiv-cs.AI | 2025-04-02 |
| 354 | 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 |
| 355 | 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 |
| 356 | Enhancing Negation Awareness in Universal Text Embeddings: A Data-efficient and Computational-efficient Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To efficiently deal with the conflict that different tasks need different trade-offs between topic and negation information among other semantic information, a data-efficient and computational-efficient embedding re-weighting method is proposed without modifying the parameters of text embedding models. |
Hongliu Cao; | arxiv-cs.CL | 2025-04-01 |
| 357 | 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: This study evaluates natural language processing approaches for detecting PTSD from clinical interview transcripts. |
Feng Chen; Dror Ben-Zeev; Gillian Sparks; Arya Kadakia; Trevor Cohen; | arxiv-cs.CL | 2025-04-01 |
| 358 | TransMamba: Flexibly Switching Between Transformer and Mamba Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes TransMamba, a novel framework that unifies Transformer and Mamba through shared parameter matrices (e.g., QKV and CBx), and thus could dynamically switch between attention and SSM mechanisms at different token lengths and layers. |
YIXING LI et. al. | arxiv-cs.LG | 2025-03-31 |
| 359 | 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 |
| 360 | LLM4FS: Leveraging Large Language Models for Feature Selection and How to Improve It Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Notably, our analysis reveals that the hybrid strategy leverages the contextual understanding of LLMs and the high statistical reliability of traditional data-driven methods to achieve excellent feature selection performance, even surpassing LLMs and traditional data-driven methods. |
Jianhao Li; Xianchao Xiu; | arxiv-cs.LG | 2025-03-31 |
| 361 | 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 |
| 362 | 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 |
| 363 | 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 |
| 364 | 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 |
| 365 | 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 |
| 366 | 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 |
| 367 | 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 |
| 368 | LaViC: Adapting Large Vision-Language Models to Visually-Aware Conversational Recommendation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Although textual information suffices for many domains, visually driven categories such as fashion or home decor potentially require detailed visual information related to color, style, or design. To address this challenge, we propose LaViC (Large Vision-Language Conversational Recommendation Framework), a novel approach that integrates compact image representations into dialogue-based recommendation systems. |
Hyunsik Jeon; Satoshi Koide; Yu Wang; Zhankui He; Julian McAuley; | arxiv-cs.AI | 2025-03-30 |
| 369 | Large Language Models Pass The Turing Test 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 |
| 370 | 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 |
| 371 | 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 |
| 372 | XL-Instruct: Synthetic Data for Cross-Lingual Open-Ended Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce XL-AlpacaEval, a new benchmark for evaluating cross-lingual generation capabilities in Large Language Models (LLMs), and propose XL-Instruct, a high-quality synthetic data generation method. |
Vivek Iyer; Ricardo Rei; Pinzhen Chen; Alexandra Birch; | arxiv-cs.CL | 2025-03-29 |
| 373 | 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 |
| 374 | 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 |
| 375 | 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. | arxiv-cs.CL | 2025-03-28 |
| 376 | 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 |
| 377 | 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 process streaming data from social media, healthcare records, and emergency services to identify overdose events. |
Grigori Sidorov; Muhammad Ahmad; Iqra Ameer; Muhammad Usman; Ildar Batyrshin; | arxiv-cs.CL | 2025-03-28 |
| 378 | 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 |
| 379 | 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 |
| 380 | 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 |
| 381 | 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 |
| 382 | 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 |
| 383 | 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 |
| 384 | 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 |
| 385 | 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 |
| 386 | 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 |
| 387 | 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 |
| 388 | 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 |
| 389 | 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 |
| 390 | 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 |
| 391 | GeoBenchX: Benchmarking LLMs for Multistep Geospatial Tasks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we establish a benchmark for evaluating large language models (LLMs) on multi-step geospatial tasks relevant to commercial GIS practitioners. |
Varvara Krechetova; Denis Kochedykov; | arxiv-cs.CL | 2025-03-23 |
| 392 | 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 |
| 393 | 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 |
| 394 | 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 |
| 395 | 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 |
| 396 | 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 |
| 397 | 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 |
| 398 | 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 |
| 399 | 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 |
| 400 | 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 |
| 401 | 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 |
| 402 | Quantization-Free Autoregressive Action Transformer Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a quantization-free method instead that leverages Generative Infinite-Vocabulary Transformers (GIVT) as a direct, continuous policy parametrization for autoregressive transformers. |
Ziyad Sheebaelhamd; Michael Tschannen; Michael Muehlebach; Claire Vernade; | arxiv-cs.LG | 2025-03-18 |
| 403 | LipShiFT: A Certifiably Robust Shift-based Vision Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Focusing on a Lipschitz continuous variant of the ShiftViT model, we address significant training challenges for transformer-based architectures under norm-constrained input setting. |
Rohan Menon; Nicola Franco; Stephan Günnemann; | arxiv-cs.LG | 2025-03-18 |
| 404 | Graph Transformers Dream of Electric Flow Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present explicit weight configurations for implementing each algorithm, and we bound the constructed Transformers’ errors by the errors of the underlying algorithms. |
Xiang Cheng; Lawrence Carin; Suvrit Sra; | iclr | 2025-03-17 |
| 405 | ExACT: Teaching AI Agents to Explore with Reflective-MCTS and Exploratory Learning 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 |
| 406 | Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens 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 |
| 407 | Forgetting Transformer: Softmax Attention with A Forget Gate 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 |
| 408 | VibeCheck: Discover and Quantify Qualitative Differences in Large Language Models 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 |
| 409 | 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 |
| 410 | Dynamic Diffusion Transformer 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 |
| 411 | 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 |
| 412 | ACE: All-round Creator and Editor Following Instructions Via Diffusion Transformer 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 |
| 413 | 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 |
| 414 | KiVA: Kid-inspired Visual Analogies for Testing Large Multimodal Models 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 |
| 415 | WorkflowLLM: Enhancing Workflow Orchestration Capability of Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To address this limitation, we present WorkflowLLM, a data-centric framework elaborately designed to enhance the capability of LLMs in workflow orchestration.Specifically, the construction process can be divided into three phases: (1) Data Collection: we collect real-world workflow data from Apple Shortcuts and RoutineHub, transcribing them into Python-style code. |
SHENGDA FAN et. al. | iclr | 2025-03-17 |
| 416 | 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 |
| 417 | Competing Large Language Models in Multi-Agent Gaming Environments 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 |
| 418 | 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 |
| 419 | A Quantum Circuit-Based Compression Perspective for Parameter-Efficient Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we introduce Quantum Parameter Adaptation (QPA) in the framework of quantum parameter generation, which integrates QNNs with a classical multi-layer perceptron mapping model to generate parameters for fine-tuning methods. |
Chen-Yu Liu; Chao-Han Huck Yang; Hsi-Sheng Goan; Min-Hsiu Hsieh; | iclr | 2025-03-17 |
| 420 | 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 |
| 421 | Motion-Agent: A Conversational Framework for Human Motion Generation with LLMs 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 |
| 422 | 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 |
| 423 | Mixture-of-Agents Enhances Large Language Model Capabilities 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 |
| 424 | 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; | arxiv-cs.CV | 2025-03-17 |
| 425 | Timer-XL: Long-Context Transformers for Unified Time Series Forecasting 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 |
| 426 | DreamBench++: A Human-Aligned Benchmark for Personalized Image Generation 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 |
| 427 | 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 |
| 428 | BriLLM: Brain-inspired Large Language Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper reports the first brain-inspired large language model (BriLLM). |
Hai Zhao; Hongqiu Wu; Dongjie Yang; Anni Zou; Jiale Hong; | arxiv-cs.CL | 2025-03-14 |
| 429 | 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 |
| 430 | 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 |
| 431 | 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 |
| 432 | 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 |
| 433 | 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 |
| 434 | 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 |
| 435 | 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 |
| 436 | 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 |
| 437 | Radar: Fast Long-Context Decoding for Any Transformer Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose Radar, a training-free approach that accelerates inference by dynamically searching for the most important context tokens. |
Yongchang Hao; Mengyao Zhai; Hossein Hajimirsadeghi; Sepidehsadat Hosseini; Frederick Tung; | arxiv-cs.LG | 2025-03-13 |
| 438 | 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 |
| 439 | 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 |
| 440 | 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 |
| 441 | 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 |
| 442 | 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 |
| 443 | 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 |
| 444 | 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 |
| 445 | 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 |
| 446 | 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 |
| 447 | 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 |
| 448 | 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 |
| 449 | 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 |
| 450 | 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 |
| 451 | 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 |
| 452 | 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 |
| 453 | 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 |
| 454 | 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 |
| 455 | 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 |
| 456 | 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 |
| 457 | 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 |
| 458 | 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 |
| 459 | 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 |
| 460 | 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 |
| 461 | Benchmarking Reasoning Robustness in Large Language Models 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 |
| 462 | 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 |
| 463 | 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 |
| 464 | 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 |
| 465 | 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 |
| 466 | 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 |
| 467 | Transformer-Based Spatio-Temporal Association of Apple Fruitlets Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present a transformer-based method to spatio-temporally associate apple fruitlets in stereo-images collected on different days and from different camera poses. |
Harry Freeman; George Kantor; | arxiv-cs.CV | 2025-03-05 |
| 468 | 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 |
| 469 | 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 |
| 470 | 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 |
| 471 | 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 |
| 472 | 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 |
| 473 | 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 |
| 474 | 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 |
| 475 | 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 |
| 476 | 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 |
| 477 | 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 |
| 478 | Forgetting Transformer: Softmax Attention with A Forget Gate 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 |
| 479 | 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 |
| 480 | 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 |
| 481 | Layered Insights: Generalizable Analysis of Authorial Style By Leveraging All Transformer Layers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a new approach for the authorship attribution task that leveragesthe various linguistic representations learned at different layers ofpre-trained transformer-based models. |
Milad Alshomary; Nikhil Reddy Varimalla; Vishal Anand; Smaranda Muresan; Kathleen McKeown; | arxiv-cs.CL | 2025-03-02 |
| 482 | 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 |
| 483 | 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 |
| 484 | 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 |
| 485 | 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 |
| 486 | 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 |
| 487 | TimesBERT: A BERT-Style Foundation Model for Time Series Understanding Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, inspired by the shared multi-granularity structure between multivariate time series and multisentence documents, we design TimesBERT to learn generic representations of time series including temporal patterns and variate-centric characteristics. |
HAORAN ZHANG et. al. | arxiv-cs.LG | 2025-02-28 |
| 488 | Fine-tuning BERT with Bidirectional LSTM for Fine-grained Movie Reviews Sentiment Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper our objective is to fine-tune the pre-trained BERT model with Bidirectional LSTM (BiLSTM) to enhance both binary and fine-grained SA specifically for movie reviews. |
Gibson Nkhata; Susan Gauch; Usman Anjum; Justin Zhan; | arxiv-cs.CL | 2025-02-27 |
| 489 | Visual Reasoning at Urban Intersections: FineTuning GPT-4o for Traffic Conflict Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Code used in this study is available at https://github.com/sarimasri3/Traffic-Intersection-Conflict-Detection-using-images.git. |
Sari Masri; Huthaifa I. Ashqar; Mohammed Elhenawy; | arxiv-cs.CV | 2025-02-27 |
| 490 | Consistency Evaluation of News Article Summaries Generated By Large (and Small) Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce a meta evaluation score which directly assesses the performance of the LLM evaluation system (prompt + model). |
Colleen Gilhuly; Haleh Shahzad; | arxiv-cs.CL | 2025-02-27 |
| 491 | Lotus at SemEval-2025 Task 11: RoBERTa with Llama-3 Generated Explanations for Multi-Label Emotion Classification Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper presents a novel approach for multi-label emotion detection, where Llama-3 is used to generate explanatory content that clarifies ambiguous emotional expressions, thereby enhancing RoBERTa’s emotion classification performance. |
Niloofar Ranjbar; Hamed Baghbani; | arxiv-cs.LG | 2025-02-27 |
| 492 | Large Language Model Strategic Reasoning Evaluation Through Behavioral Game Theory Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Strategic decision-making involves interactive reasoning where agents adapt their choices in response to others, yet existing evaluations of large language models (LLMs) often emphasize Nash Equilibrium (NE) approximation, overlooking the mechanisms driving their strategic choices. To bridge this gap, we introduce an evaluation framework grounded in behavioral game theory, disentangling reasoning capability from contextual effects. |
Jingru Jia; Zehua Yuan; Junhao Pan; Paul E. McNamara; Deming Chen; | arxiv-cs.AI | 2025-02-27 |
| 493 | NeoBERT: A Next-Generation BERT Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In contrast, encoders like BERT and RoBERTa have not seen the same level of progress despite being foundational for many downstream NLP applications. To bridge this gap, we introduce NeoBERT, a next-generation encoder that redefines the capabilities of bidirectional models by integrating state-of-the-art advancements in architecture, modern data, and optimized pre-training methodologies. |
Lola Le Breton; Quentin Fournier; Mariam El Mezouar; John X. Morris; Sarath Chandar; | arxiv-cs.CL | 2025-02-26 |
| 494 | Improving Representation Learning of Complex Critical Care Data with ICU-BERT Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce ICU-BERT, a transformer-based model pre-trained on the MIMIC-IV database using a multi-task scheme to learn robust representations of complex ICU data with minimal preprocessing. |
Ricardo Santos; André V. Carreiro; Xi Peng; Hugo Gamboa; Holger Fröhlich; | arxiv-cs.LG | 2025-02-26 |
| 495 | Can Large Language Models Outperform Non-Experts in Poetry Evaluation? A Comparative Study Using The Consensual Assessment Technique Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The Consensual Assessment Technique (CAT) evaluates creativity through holistic expert judgments. |
Piotr Sawicki; Marek Grześ; Dan Brown; Fabrício Góes; | arxiv-cs.CL | 2025-02-26 |
| 496 | Enhanced Transformer-Based Tracking for Skiing Events: Overcoming Multi-Camera Challenges, Scale Variations and Rapid Motion — SkiTB Visual Tracking Challenge 2025 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we used STARK (Spatio-Temporal Transformer Network for Visual Tracking), a transformer-based model, to track skiers. |
Akhil Penta; Vaibhav Adwani; Ankush Chopra; | arxiv-cs.CV | 2025-02-26 |
| 497 | Negation-Induced Forgetting in LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The study explores whether Large Language Models (LLMs) exhibit negation-induced forgetting (NIF), a cognitive phenomenon observed in humans where negating incorrect attributes of an object or event leads to diminished recall of this object or event compared to affirming correct attributes (Mayo et al., 2014; Zang et al., 2023). |
Francesca Capuano; Ellen Boschert; Barbara Kaup; | arxiv-cs.CL | 2025-02-26 |
| 498 | Cognitive Networks Highlight Differences and Similarities in The STEM Mindsets of Human and LLM-simulated Trainees, Experts and Academics Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study uses behavioural forma mentis networks (BFMNs) to investigate the STEM-focused mindset, i.e. ways of associating and perceiving ideas, of 177 human participants and 177 artificial humans simulated by GPT-3.5. |
EDITH HAIM et. al. | arxiv-cs.CL | 2025-02-26 |
| 499 | Unleashing The Temporal-Spatial Reasoning Capacity of GPT for Training-Free Audio and Language Referenced Video Object Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose an Audio-Language-Referenced SAM 2 (AL-Ref-SAM 2) pipeline to explore the training-free paradigm for audio and language-referenced video object segmentation, namely AVS and RVOS tasks. |
SHAOFEI HUANG et. al. | aaai | 2025-02-25 |
| 500 | Independent Mobility GPT (IDM-GPT): A Self-Supervised Multi-Agent Large Language Model Framework for Customized Traffic Mobility Analysis Using Machine Learning Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Additionally, privacy issues are a major concern when processing data for real-world traffic control and management. To address these challenges, the research team proposes an innovative Multi-agent framework named Independent Mobility GPT (IDM-GPT) based on large language models (LLMs) for customized traffic analysis, management suggestions, and privacy preservation. |
Fengze Yang; Xiaoyue Cathy Liu; Lingjiu Lu; Bingzhang Wang; Chenxi Dylan Liu; | arxiv-cs.AI | 2025-02-25 |
| 501 | LLaVA Needs More Knowledge: Retrieval Augmented Natural Language Generation with Knowledge Graph for Explaining Thoracic Pathologies Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The KG datastore is designed as a plug-and-play module, allowing for seamless integration with various model architectures. We introduce and evaluate three distinct frameworks within this paradigm: KG-LLaVA, which integrates the pre-trained LLaVA model with KG-RAG; Med-XPT, a custom framework combining MedCLIP, a transformer-based projector, and GPT-2; and Bio-LLaVA, which adapts LLaVA by incorporating the Bio-ViT-L vision model. |
Ameer Hamza; Yong Hyun Ahn; Sungyoung Lee; Seong Tae Kim; | aaai | 2025-02-25 |
| 502 | Spiking Point Transformer for Point Cloud Classification Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce the Hybrid Dynamics Integrate-and-Fire Neuron (HD-IF), designed to simulate selective neuron activation and reduce over-reliance on specific artificial neurons. |
PEIXI WU et. al. | aaai | 2025-02-25 |
| 503 | Neural Reasoning for Sure Through Constructing Explainable Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Here, we introduce set-theoretic relations explicitly and seamlessly into neural networks by extending vector embedding into sphere embedding, so that part-whole relations can explicitly encode set-theoretic relations through sphere boundaries in the vector space. |
Tiansi Dong; Mateja Jamnik; Pietro Liò; | aaai | 2025-02-25 |
| 504 | CAD-GPT: Synthesising CAD Construction Sequence with Spatial Reasoning-Enhanced Multimodal LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work introduces CAD-GPT, a CAD synthesis method with spatial reasoning-enhanced MLLM that takes either a single image or a textual description as input. |
SIYU WANG et. al. | aaai | 2025-02-25 |
| 505 | DAPoinTr: Domain Adaptive Point Transformer for Point Cloud Completion Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To this end, we propose a pioneering Domain Adaptive Point Transformer (DAPoinTr) framework for point cloud completion. |
YINGHUI LI et. al. | aaai | 2025-02-25 |
| 506 | On The Power of Convolution-Augmented Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, recent architectural recipes, such as state-space models, have bridged the performance gap. Motivated by this, we examine the benefits of Convolution-Augmented Transformer (CAT) for recall, copying, and length generalization tasks. |
Mingchen Li; Xuechen Zhang; Yixiao Huang; Samet Oymak; | aaai | 2025-02-25 |
| 507 | GARLIC: GPT-Augmented Reinforcement Learning with Intelligent Control for Vehicle Dispatching Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: These challenges have resulted in travel difficulties for passengers in certain areas, while many drivers in other areas are unable to secure orders, leading to a decline in the overall quality of urban transportation services. To address these issues, this paper introduces GARLIC: a framework of GPT-Augmented Reinforcement Learning with Intelligent Control for vehicle dispatching. |
XIAO HAN et. al. | aaai | 2025-02-25 |
| 508 | The Illusion of Empathy: How AI Chatbots Shape Conversation Perception Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This study examines how chatbot identity and perceived empathy influence users’ overall conversation experience. |
TINGTING LIU et. al. | aaai | 2025-02-25 |
| 509 | Sentiment Analysis of Texts from Social Networks Based on Machine Learning Methods for Monitoring Public Sentiment Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: A sentiment analysis system powered by machine learning was created in this study to improve real-time social network public opinion monitoring. |
Arsen Tolebay Nurlanuly; | arxiv-cs.CL | 2025-02-24 |
| 510 | A Transformer-in-Transformer Network Utilizing Knowledge Distillation for Image Recognition Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a novel knowledge distillation neural architecture leveraging efficient transformer networks for effective image classification. |
Dewan Tauhid Rahman; Yeahia Sarker; Antar Mazumder; Md. Shamim Anower; | arxiv-cs.CV | 2025-02-23 |
| 511 | VPNeXt — Rethinking Dense Decoding for Plain Vision Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present VPNeXt, a new and simple model for the Plain Vision Transformer (ViT). |
Xikai Tang; Ye Huang; Guangqiang Yin; Lixin Duan; | arxiv-cs.CV | 2025-02-23 |
| 512 | Energy-Efficient Transformer Inference: Optimization Strategies for Time Series Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Our study presents a systematic investigation of optimization techniques, focusing on structured pruning and quantization methods for transformer architectures. |
Arshia Kermani; Ehsan Zeraatkar; Habib Irani; | arxiv-cs.LG | 2025-02-23 |
| 513 | Layer-Wise Evolution of Representations in Fine-Tuned Transformers: Insights from Sparse AutoEncoders Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper explores the underlying mechanisms of fine-tuning, specifically in the BERT transformer, by analyzing activation similarity, training Sparse AutoEncoders (SAEs), and visualizing token-level activations across different layers. |
Suneel Nadipalli; | arxiv-cs.CL | 2025-02-23 |
| 514 | Reasoning About Affordances: Causal and Compositional Reasoning in LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In Experiment 2, we introduced two new conditions, Distractor (more object choices, increasing difficulty) and Image (object options presented visually), and evaluated Claude 3 Sonnet and Claude 3.5 Sonnet in addition to the GPT models. |
Magnus F. Gjerde; Vanessa Cheung; David Lagnado; | arxiv-cs.AI | 2025-02-23 |
| 515 | Actionable Help in Crises: A Novel Dataset and Resource-Efficient Models for Identifying Request and Offer Social Media Posts Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Moreover, although distilled variants (e.g., DistilBERT) exist, they are not tailored for the crisis domain. To address these challenges, we make two key contributions. First, we present CrisisHelpOffer, a novel dataset of 101k tweets collaboratively labelled by generative LLMs and validated by humans, specifically designed to distinguish actionable content from noise. |
Rabindra Lamsal; Maria Rodriguez Read; Shanika Karunasekera; Muhammad Imran; | arxiv-cs.CL | 2025-02-23 |
| 516 | Iterative Auto-Annotation for Scientific Named Entity Recognition Using BERT-Based Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents an iterative approach to performing Scientific Named Entity Recognition (SciNER) using BERT-based models. |
Kartik Gupta; | arxiv-cs.CL | 2025-02-22 |
| 517 | A Close Look at Decomposition-based XAI-Methods for Transformer Language Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: One class of methods that seems very promising in this direction includes decomposition-based approaches, i.e., XAI-methods that redistribute the model’s prediction logit through the network, as this value is directly related to the prediction. In the previous literature we note though that two prominent methods of this category, namely ALTI-Logit and LRP, have not yet been analyzed in juxtaposition and hence we propose to close this gap by conducting a careful quantitative evaluation w.r.t. ground truth annotations on a subject-verb agreement task, as well as various qualitative inspections, using BERT, GPT-2 and LLaMA-3 as a testbed. |
Leila Arras; Bruno Puri; Patrick Kahardipraja; Sebastian Lapuschkin; Wojciech Samek; | arxiv-cs.CL | 2025-02-21 |
| 518 | Comparative Analysis of Large Language Models for Context-Aware Code Completion Using SAFIM Framework Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work provides a comparative analysis that underscores the trade-offs between accuracy and speed, establishing a benchmark for future advancements in LLM-based code completion. |
HANG ZHANG et. al. | arxiv-cs.SE | 2025-02-21 |
| 519 | 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 Carrie Wu; Zhe Wang; Dmitriy Bespalov; Yanjun Qi; | arxiv-cs.CR | 2025-02-21 |
| 520 | Single-pass Detection of Jailbreaking Input in Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Instead, we focus on detecting jailbreaking input in a single forward pass. |
Leyla Naz Candogan; Yongtao Wu; Elias Abad Rocamora; Grigorios G. Chrysos; Volkan Cevher; | arxiv-cs.LG | 2025-02-21 |
| 521 | MutaGReP: Execution-Free Repository-Grounded Plan Search for Code-Use Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose MutaGReP (Mutation-guided Grounded Repository Plan Search), an approach to search for plans that decompose a user request into natural language steps grounded in the codebase. |
ZAID KHAN et. al. | arxiv-cs.CL | 2025-02-21 |
| 522 | 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 innovative privacy-preserving federated framework specifically designed for compressing LLMs into task-specific SLMs via pruning and Chain-of-Thought (COT) distillation. |
TAO FAN et. al. | arxiv-cs.CL | 2025-02-21 |
| 523 | Robust Bias Detection in MLMs and Its Application to Human Trait Ratings Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Addressing these, we propose a systematic statistical approach to assess bias in MLMs, using mixed models to account for random effects, pseudo-perplexity weights for sentences derived from templates and quantify bias using statistical effect sizes. |
Ingroj Shrestha; Louis Tay; Padmini Srinivasan; | arxiv-cs.CL | 2025-02-21 |
| 524 | Cross-Format Retrieval-Augmented Generation in XR with LLMs for Context-Aware Maintenance Assistance Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a detailed evaluation of a Retrieval-Augmented Generation (RAG) system that integrates large language models (LLMs) to enhance information retrieval and instruction generation for maintenance personnel across diverse data formats. |
Akos Nagy; Yannis Spyridis; Vasileios Argyriou; | arxiv-cs.IR | 2025-02-21 |
| 525 | Extraction Multi-étiquettes De Relations En Utilisant Des Couches De Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this article, we present the BTransformer18 model, a deep learning architecture designed for multi-label relation extraction in French texts. |
Ngoc Luyen Le; Gildas Tagny Ngompé; | arxiv-cs.CL | 2025-02-21 |
| 526 | 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). |
Xiaoyu Chen; Changde Du; Che Liu; Yizhe Wang; Huiguang He; | arxiv-cs.HC | 2025-02-20 |
| 527 | Generative Adversarial Networks Vs Large Language Models: A Comparative Study on Synthetic Tabular Data Generation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a new framework for zero-shot generation of synthetic tabular data. |
Austin A. Barr; Robert Rozman; Eddie Guo; | arxiv-cs.LG | 2025-02-20 |
| 528 | Leveraging ChatGPT for Sponsored Ad Detection and Keyword Extraction in YouTube Videos Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work-in-progress paper presents a novel approach to detecting sponsored advertisement segments in YouTube videos and comparing the advertisement with the main content. |
Brice Valentin Kok-Shun; Johnny Chan; | arxiv-cs.LG | 2025-02-20 |
| 529 | Extracting Social Connections from Finnish Karelian Refugee Interviews Using LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We find that the best generative model (GPT-4) is roughly on par with human performance, at an F-score of 88.8%. |
Joonatan Laato; Jenna Kanerva; John Loehr; Virpi Lummaa; Filip Ginter; | arxiv-cs.CL | 2025-02-19 |
| 530 | DeepSeek-V3, GPT-4, Phi-4, and LLaMA-3.3 Generate Correct Code for LoRaWAN-related Engineering Tasks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper investigates the performance of 16 Large Language Models (LLMs) in automating LoRaWAN-related engineering tasks involving optimal placement of drones and received power calculation under progressively complex zero-shot, natural language prompts. |
Daniel Fernandes; João P. Matos-Carvalho; Carlos M. Fernandes; Nuno Fachada; | arxiv-cs.SE | 2025-02-19 |
| 531 | UM_FHS at TREC 2024 PLABA: Exploration of Fine-tuning and AI Agent Approach for Plain Language Adaptations of Biomedical Text Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper describes our submissions to the TREC 2024 PLABA track with the aim to simplify biomedical abstracts for a K8-level audience (13-14 years old students). |
PRIMOZ KOCBEK et. al. | arxiv-cs.CL | 2025-02-19 |
| 532 | Inner Thinking Transformer: Leveraging Dynamic Depth Scaling to Foster Adaptive Internal Thinking 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. | arxiv-cs.CL | 2025-02-19 |
| 533 | Learning Novel Transformer Architecture for Time-series Forecasting Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Despite the success of Transformer-based models in the time-series prediction (TSP) tasks, the existing Transformer architecture still face limitations and the literature lacks comprehensive explorations into alternative architectures. To address these challenges, we propose AutoFormer-TS, a novel framework that leverages a comprehensive search space for Transformer architectures tailored to TSP tasks. |
Juyuan Zhang; Wei Zhu; Jiechao Gao; | arxiv-cs.LG | 2025-02-19 |
| 534 | QUAD-LLM-MLTC: Large Language Models Ensemble Learning for Healthcare Text Multi-Label Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, when dealing with various labels, different prompts can be relevant depending on the topic. To address these challenges, the proposed approach, QUAD-LLM-MLTC, leverages the strengths of four LLMs: GPT-4o, BERT, PEGASUS, and BART. |
Hajar Sakai; Sarah S. Lam; | arxiv-cs.CL | 2025-02-19 |
| 535 | Simulating User Diversity in Task-Oriented Dialogue Systems Using Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we explore the application of Large Language Models (LLMs) for generating synthetic users and simulating user conversations with a task-oriented dialogue system and present detailed results and their analysis. |
Adnan Ahmad; Stefan Hillmann; Sebastian Möller; | arxiv-cs.CL | 2025-02-18 |
| 536 | Language Models Are Few-Shot Graders Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present an ASAG pipeline leveraging state-of-the-art LLMs. |
Chenyan Zhao; Mariana Silva; Seth Poulsen; | arxiv-cs.CL | 2025-02-18 |
| 537 | 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. |
YONG ZHANG et. al. | arxiv-cs.CL | 2025-02-18 |
| 538 | An LLM-Powered Agent for Physiological Data Analysis: A Case Study on PPG-based Heart Rate Estimation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we develop an LLM-powered agent for physiological time-series analysis aimed to bridge the gap in integrating LLMs with well-established analytical tools. |
Mohammad Feli; Iman Azimi; Pasi Liljeberg; Amir M. Rahmani; | arxiv-cs.CL | 2025-02-18 |
| 539 | 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 Treviso; André F. T. Martins; | arxiv-cs.CL | 2025-02-17 |
| 540 | GLoT: A Novel Gated-Logarithmic Transformer for Efficient Sign Language Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel Gated-Logarithmic Transformer (GLoT) that captures the long-term temporal dependencies of the sign language as a time-series data. |
Nada Shahin; Leila Ismail; | arxiv-cs.CL | 2025-02-17 |
| 541 | Mixture of Attention Yields Accurate Results for Tabular Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To bridge the gap, we propose MAYA, an encoder-decoder transformer-based framework. |
XUECHEN LI et. al. | arxiv-cs.LG | 2025-02-17 |
| 542 | 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; | arxiv-cs.CL | 2025-02-17 |
| 543 | Positional Encoding in Transformer-Based Time Series Models: A Survey Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Recent advancements in transformer-based models have greatly improved time series analysis, providing robust solutions for tasks such as forecasting, anomaly detection, and classification. |
Habib Irani; Vangelis Metsis; | arxiv-cs.LG | 2025-02-17 |
| 544 | The Geometry of BERT Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, their internal mechanisms remain mathematically obscure, highlighting the need for greater explainability and interpretability. In this direction, this paper investigates the internal mechanisms of BERT proposing a novel perspective on the attention mechanism of BERT from a theoretical perspective. |
Matteo Bonino; Giorgia Ghione; Giansalvo Cirrincione; | arxiv-cs.LG | 2025-02-17 |
| 545 | Building A Proof-Oriented Programmer That Is 64% Better Than GPT-4o Under Data Scarsity Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present the first on synthetic data augmentation for project level proof oriented programming for both generation and repair. |
Dylan Zhang; Justin Wang; Tianran Sun; | arxiv-cs.CL | 2025-02-17 |
| 546 | Vendi-RAG: Adaptively Trading-Off Diversity And Quality Significantly Improves Retrieval Augmented Generation With LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces Vendi-RAG, a framework based on an iterative process that jointly optimizes retrieval diversity and answer quality. |
Mohammad Reza Rezaei; Adji Bousso Dieng; | arxiv-cs.CL | 2025-02-16 |
| 547 | Faces of Fairness: Examining Bias in Facial Expression Recognition Datasets and Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study investigates bias sources in FER datasets and models. |
Mohammad Mehdi Hosseini; Ali Pourramezan Fard; Mohammad H. Mahoor; | arxiv-cs.CV | 2025-02-16 |
| 548 | Performance Review on LLM for Solving Leetcode Problems Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a comprehensive performance evaluation of Large Language Models (LLMs) in solving programming challenges from Leetcode, a widely used platform for algorithm practice and technical interviews. |
LUN WANG et. al. | arxiv-cs.SE | 2025-02-16 |
| 549 | ANCHOLIK-NER: A Benchmark Dataset for Bangla Regional Named Entity Recognition Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: While NER systems for Standard Bangla have made progress, no existing resources or models specifically address the challenge of regional dialects such as Barishal, Chittagong, Mymensingh, Noakhali, and Sylhet, which exhibit unique linguistic features that existing models fail to handle effectively. To fill this gap, we introduce ANCHOLIK-NER, the first benchmark dataset for NER in Bangla regional dialects, comprising 17,405 sentences distributed across five regions. |
BIDYARTHI PAUL et. al. | arxiv-cs.CL | 2025-02-16 |
| 550 | Integrating Language Models for Enhanced Network State Monitoring in DRL-Based SFC Provisioning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper integrates DRL with Language Models (LMs), specifically Bidirectional Encoder Representations from Transformers (BERT) and DistilBERT, to enhance network management. |
Parisa Fard Moshiri; Murat Arda Onsu; Poonam Lohan; Burak Kantarci; Emil Janulewicz; | arxiv-cs.NI | 2025-02-16 |
| 551 | Distraction Is All You Need for Multimodal Large Language Model Jailbreaking Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To address this, we analyze the relationship between image content and task and find that the complexity of subimages, rather than their content, is key. Building on this insight, we propose the Distraction Hypothesis, followed by a novel framework called Contrasting Subimage Distraction Jailbreaking (CS-DJ), to achieve jailbreaking by disrupting MLLMs alignment through multi-level distraction strategies. |
ZUOPENG YANG et. al. | arxiv-cs.CV | 2025-02-15 |
| 552 | 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 Sager; Pau Vilimelis Aceituno; Thilo Stadelmann; Benjamin Grewe; | arxiv-cs.LG | 2025-02-15 |
| 553 | Empirical Evaluation of LLMs in Predicting Fixes of Configuration Bugs in Smart Home System Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This empirical study evaluates the effectiveness of Large Language Models (LLMs) in predicting fixes for configuration bugs in smart home systems. |
Sheikh Moonwara Anjum Monisha; Atul Bharadwaj; | arxiv-cs.SE | 2025-02-15 |
| 554 | A Preliminary Exploration with GPT-4o Voice Mode Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: With the rise of multimodal large language models, GPT-4o stands out as a pioneering model, driving us to evaluate its capabilities. This report assesses GPT-4o across various tasks to analyze its audio processing and reasoning abilities. |
YU-XIANG LIN et. al. | arxiv-cs.CL | 2025-02-14 |
| 555 | Do Large Language Models Reason Causally Like Us? Even Better? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Large language models (LLMs) have shown impressive capabilities in generating human-like text, raising questions about whether their responses reflect true understanding or statistical patterns. |
Hanna M. Dettki; Brenden M. Lake; Charley M. Wu; Bob Rehder; | arxiv-cs.AI | 2025-02-14 |
| 556 | Large Language Diffusion Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: By optimizing a likelihood bound, it provides a principled generative approach for probabilistic inference. |
SHEN NIE et. al. | arxiv-cs.CL | 2025-02-14 |
| 557 | Code-Mixed Telugu-English Hate Speech Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study investigates transformer-based models, including TeluguHateBERT, HateBERT, DeBERTa, Muril, IndicBERT, Roberta, and Hindi-Abusive-MuRIL, for classifying hate speech in Telugu. |
Santhosh Kakarla; Gautama Shastry Bulusu Venkata; | arxiv-cs.CL | 2025-02-14 |
| 558 | An Innovative Next Activity Prediction Approach Using Process Entropy and DAW-Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes an entropy-driven model selection approach and DAW-Transformer, which stands for Dynamic Attribute-Aware Transformer, to integrate all attributes with a dynamic window for better accuracy. |
Hadi Zare; Mostafa Abbasi; Maryam Ahang; Homayoun Najjaran; | arxiv-cs.LG | 2025-02-14 |
| 559 | 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. | arxiv-cs.CL | 2025-02-13 |
| 560 | Zero-shot Generation of Synthetic Neurosurgical Data with Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This study aims to evaluate the capability of zero-shot generation of synthetic neurosurgical data with a large language model (LLM), GPT-4o, by benchmarking with the conditional tabular generative adversarial network (CTGAN). |
Austin A. Barr; Eddie Guo; Emre Sezgin; | arxiv-cs.CL | 2025-02-13 |
| 561 | Evaluating GPT’s Capability in Identifying Stages of Cognitive Impairment from Electronic Health Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Information about cognitive impairment often exists within unstructured clinician notes in EHRs, but manual chart reviews are both time-consuming and error-prone. To address this issue, our study evaluates an automated approach using zero-shot GPT-4o to determine stage of cognitive impairment in two different tasks. |
YU LENG et. al. | arxiv-cs.LG | 2025-02-13 |
| 562 | AttentionSmithy: A Modular Framework for Rapid Transformer Development and Customization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce AttentionSmithy, a modular software package that simplifies transformer innovation by breaking down key components into reusable building blocks: attention modules, feed-forward networks, normalization layers, and positional encodings. |
Caleb Cranney; Jesse G. Meyer; | arxiv-cs.LG | 2025-02-13 |
| 563 | APT-LLM: Embedding-Based Anomaly Detection of Cyber Advanced Persistent Threats Using Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces APT-LLM, a novel embedding-based anomaly detection framework that integrates large language models (LLMs) — BERT, ALBERT, DistilBERT, and RoBERTa — with autoencoder architectures to detect APTs. |
Sidahmed Benabderrahmane; Petko Valtchev; James Cheney; Talal Rahwan; | arxiv-cs.CR | 2025-02-13 |
| 564 | Mechanistic Unveiling of Transformer Circuits: Self-Influence As A Key to Model Reasoning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: It is still unclear which multi-step reasoning mechanisms are used by language models to solve such tasks. In this paper, we aim to address this question by investigating the mechanistic interpretability of language models, particularly in the context of multi-step reasoning tasks. |
Lin Zhang; Lijie Hu; Di Wang; | arxiv-cs.AI | 2025-02-13 |
| 565 | MTDP: A Modulated Transformer Based Diffusion Policy Model Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we investigate key architectural designs of Transformers and improve the traditional Transformer architecture by proposing the Modulated Transformer Diffusion Policy (MTDP) model for diffusion policy. |
Qianhao Wang; Yinqian Sun; Enmeng Lu; Qian Zhang; Yi Zeng; | arxiv-cs.RO | 2025-02-13 |
| 566 | A Hybrid Transformer Model for Fake News Detection: Leveraging Bayesian Optimization and Bidirectional Recurrent Unit Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose an optimized Transformer model that integrates Bayesian algorithms with a Bidirectional Gated Recurrent Unit (BiGRU), and apply it to fake news classification for the first time. |
Tianyi Huang; Zeqiu Xu; Peiyang Yu; Jingyuan Yi; Xiaochuan Xu; | arxiv-cs.CL | 2025-02-13 |
| 567 | Toward Total Recall: Enhancing FAIRness Through AI-Driven Metadata Standardization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present a method that combines GPT-4 with structured metadata templates from the CEDAR knowledge base to automatically standardize metadata and to ensure compliance with established standards. |
Sowmya S Sundaram; Rafael S. Gonçalves; Mark A Musen; | arxiv-cs.IR | 2025-02-13 |
| 568 | Optimizing GPT for Video Understanding: Zero-Shot Performance and Prompt Engineering Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we tackle industry challenges in video content classification by exploring and optimizing GPT-based models for zero-shot classification across seven critical categories of video quality. |
Mark Beliaev; Victor Yang; Madhura Raju; Jiachen Sun; Xinghai Hu; | arxiv-cs.CV | 2025-02-13 |
| 569 | Application of Tabular Transformer Architectures for Operating System Fingerprinting Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This study investigates the application of Tabular Transformer architectures-specifically TabTransformer and FT-Transformer-for OS fingerprinting, leveraging structured network data from three publicly available datasets. |
Rubén Pérez-Jove; Cristian R. Munteanu; Alejandro Pazos; Jose Vázquez-Naya; | arxiv-cs.CR | 2025-02-13 |
| 570 | Evaluating GPT for Use in K-12 Block Based CS Instruction Using A Transpiler and Prompt Engineering Related Papers Related Patents Related Grants Related Venues Related Experts View |
David Gonzalez-Maldonado; Jonathan Liu; Diana Franklin; | Technical Symposium on Computer Science Education | 2025-02-12 |
| 571 | Democratizing AI: Open-source Scalable LLM Training on GPU-based Supercomputers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we present a novel four-dimensional hybrid parallel algorithm implemented in a highly scalable, portable, open-source framework called AxoNN. |
SIDDHARTH SINGH et. al. | arxiv-cs.LG | 2025-02-12 |
| 572 | Cancer Vaccine Adjuvant Name Recognition from Biomedical Literature Using Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Future work aims to broaden the framework to encompass various biomedical literature and enhance model generalizability across various vaccines and adjuvants. |
HASIN REHANA et. al. | arxiv-cs.CL | 2025-02-12 |
| 573 | 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; | arxiv-cs.CL | 2025-02-12 |
| 574 | FoQA: A Faroese Question-Answering Dataset Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present FoQA, a Faroese extractive question-answering (QA) dataset with 2,000 samples, created using a semi-automated approach combining Large Language Models (LLMs) and human validation. |
Annika Simonsen; Dan Saattrup Nielsen; Hafsteinn Einarsson; | arxiv-cs.CL | 2025-02-11 |
| 575 | WHODUNIT: Evaluation Benchmark for Culprit Detection in Mystery Stories Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present a novel data set, WhoDunIt, to assess the deductive reasoning capabilities of large language models (LLM) within narrative contexts. |
Kshitij Gupta; | arxiv-cs.CL | 2025-02-11 |
| 576 | Large Language Models Perpetuate Bias in Palliative Care: Development and Analysis of The Palliative Care Adversarial Dataset (PCAD) Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Bias and inequity in palliative care disproportionately affect marginalised groups. Large language models (LLMs), such as GPT-4o, hold potential to enhance care but risk … |
NAOMI AKHRAS et. al. | arxiv-cs.CY | 2025-02-11 |
| 577 | RideKE: Leveraging Low-Resource, User-Generated Twitter Content for Sentiment and Emotion Detection in Kenyan Code-Switched Dataset Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We detail the methodology behind data collection and annotation, and the challenges encountered during the data curation phase. |
Naome A. Etori; Maria L. Gini; | arxiv-cs.CL | 2025-02-10 |
| 578 | A Large-Scale Benchmark for Vietnamese Sentence Paraphrases Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper presents ViSP, a high-quality Vietnamese dataset for sentence paraphrasing, consisting of 1.2M original-paraphrase pairs collected from various domains. |
Sang Quang Nguyen; Kiet Van Nguyen; | arxiv-cs.CL | 2025-02-10 |
| 579 | Leveraging GPT-4o Efficiency for Detecting Rework Anomaly in Business Processes Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper investigates the effectiveness of GPT-4o-2024-08-06, one of the Large Language Models (LLM) from OpenAI, in detecting business process anomalies, with a focus on rework anomalies. |
Mohammad Derakhshan; Paolo Ceravolo; Fatemeh Mohammadi; | arxiv-cs.LG | 2025-02-10 |
| 580 | Benchmarking Prompt Engineering Techniques for Secure Code Generation with GPT Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, its effectiveness in mitigating vulnerabilities in LLM-generated code remains underexplored. To address this gap, we implemented a benchmark to automatically assess the impact of various prompt engineering strategies on code security. |
Marc Bruni; Fabio Gabrielli; Mohammad Ghafari; Martin Kropp; | arxiv-cs.SE | 2025-02-09 |
| 581 | Online Social Support Detection in Spanish Social Media Texts Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study proposes an innovative approach to detecting online social support in Spanish-language social media texts. |
MOEIN SHAHIKI TASH et. al. | arxiv-cs.CL | 2025-02-09 |
| 582 | Provably Overwhelming Transformer Models with Designed Inputs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We develop an algorithm which, given a trained transformer model $\mathcal{M}$ as input, as well as a string of tokens $s$ of length $n_{fix}$ and an integer $n_{free}$, can generate a mathematical proof that $\mathcal{M}$ is “overwhelmed” by $s$, in time and space $\widetilde{O}(n_{fix}^2 + n_{free}^3)$. |
Lev Stambler; Seyed Sajjad Nezhadi; Matthew Coudron; | arxiv-cs.LG | 2025-02-09 |
| 583 | Flowing Through Layers: A Continuous Dynamical Systems Perspective on Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We show that the standard discrete update rule of transformer layers can be naturally interpreted as a forward Euler discretization of a continuous dynamical system. |
Jacob Fein-Ashley; | arxiv-cs.LG | 2025-02-08 |
| 584 | EAP-GP: Mitigating Saturation Effect in Gradient-based Automated Circuit Identification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we revisit existing gradient-based circuit identification methods and find that their performance is either affected by the zero-gradient problem or saturation effects, where edge attribution scores become insensitive to input changes, resulting in noisy and unreliable attribution evaluations for circuit components. |
LIN ZHANG et. al. | arxiv-cs.LG | 2025-02-07 |
| 585 | Vision-Integrated LLMs for Autonomous Driving Assistance : Human Performance Comparison and Trust Evaluation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In response, this study introduces a Large Language Model (LLM)-based Autonomous Driving (AD) assistance system that integrates a vision adapter and an LLM reasoning module to enhance visual understanding and decision-making. |
Namhee Kim; Woojin Park; | arxiv-cs.CV | 2025-02-06 |
| 586 | Lowering The Barrier of Machine Learning: Achieving Zero Manual Labeling in Review Classification Using LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces an approach that integrates large language models (LLMs), specifically Generative Pre-trained Transformer (GPT) and Bidirectional Encoder Representations from Transformers (BERT)-based models, making it accessible to a wider audience. |
Yejian Zhang; Shingo Takada; | arxiv-cs.CL | 2025-02-05 |
| 587 | FewTopNER: Integrating Few-Shot Learning with Topic Modeling and Named Entity Recognition in A Multilingual Framework Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce FewTopNER, a novel framework that integrates few-shot named entity recognition (NER) with topic-aware contextual modeling to address the challenges of cross-lingual and low-resource scenarios. |
Ibrahim Bouabdallaoui; Fatima Guerouate; Samya Bouhaddour; Chaimae Saadi; Mohammed Sbihi; | arxiv-cs.CL | 2025-02-04 |
| 588 | A Systematic Approach for Assessing Large Language Models’ Test Case Generation Capability Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To address the assessment of LLM’s test case generation ability and lacking dataset for evaluation, we propose the Generated Benchmark from Control-Flow Structure and Variable Usage Composition (GBCV) approach, which systematically generates programs used for evaluating LLMs’ test generation capabilities. |
Hung-Fu Chang; Mohammad Shokrolah Shirazi; | arxiv-cs.SE | 2025-02-04 |
| 589 | Aligning Human and Machine Attention for Enhanced Supervised Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Given that humans continue to outperform machines in certain learning tasks, it seems plausible that machine performance could be enriched by aligning machine attention with human attention mechanisms — yet research on this topic is sparse and has achieved only limited success. This paper proposes a new approach to address this gap, called Human-Machine Attention Learning (HuMAL). |
Avihay Chriqui; Inbal Yahav; Dov Teeni; Ahmed Abbasi; | arxiv-cs.LG | 2025-02-04 |
| 590 | Annotation Tool and Dataset for Fact-Checking Podcasts Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Fact-checking podcasts is a challenging task, requiring transcription, annotation, and claim verification, all while preserving the contextual details of spoken content. Our tool offers a novel approach to tackle these challenges by enabling real-time annotation of podcasts during playback. |
Vinay Setty; Adam James Becker; | arxiv-cs.CL | 2025-02-03 |
| 591 | Towards Safer Chatbots: A Framework for Policy Compliance Evaluation of Custom GPTs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, their black-box nature introduces significant safety and compliance risks. In this work, we present a scalable framework for the automated evaluation of Custom GPTs against OpenAI’s usage policies, which define the permissible behaviors of these systems. |
David Rodriguez; William Seymour; Jose M. Del Alamo; Jose Such; | arxiv-cs.CL | 2025-02-03 |
| 592 | Explainable Sentiment Analysis with DeepSeek-R1: Performance, Efficiency, and Few-Shot Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study presents the first comprehensive evaluation ofDeepSeek-R1–an open-source reasoning model–against OpenAI’s GPT-4o andGPT-4o-mini. |
Donghao Huang; Zhaoxia Wang; | arxiv-cs.CL | 2025-02-03 |
| 593 | Optimal Sensor Placement in Power Transformers Using Physics-Informed Neural Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Our work aims at simulating and predicting the temperature conditions inside a power transformer using Physics-Informed Neural Networks (PINNs). |
Sirui Li; Federica Bragone; Matthieu Barreau; Tor Laneryd; Kateryna Morozovska; | arxiv-cs.LG | 2025-02-01 |
| 594 | Explainable AI for Sentiment Analysis of Human Metapneumovirus (HMPV) Using XLNet Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We apply transformer models, particularly XLNet, achieving 93.50% accuracy in sentiment classification. |
Md. Shahriar Hossain Apu; Md Saiful Islam; Tanjim Taharat Aurpa; | arxiv-cs.CL | 2025-02-01 |
| 595 | Large Language Models’ Accuracy in Emulating Human Experts’ Evaluation of Public Sentiments About Heated Tobacco Products on Social Media Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study examined the accuracy of LLMs in replicating human sentiment evaluation of social media messages about heated tobacco products (HTPs). |
Kwanho Kim; Soojong Kim; | arxiv-cs.CL | 2025-01-31 |
| 596 | Structure Development in List-Sorting Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Interestingly, vocabulary-splitting is present regardless of whether we use weight decay, a common regularization technique thought to drive simplification, supporting the thesis that neural networks naturally prefer simpler solutions. |
Einar Urdshals; Jasmina Urdshals; | arxiv-cs.LG | 2025-01-30 |
| 597 | A Multi-Layered Large Language Model Framework for Disease Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study explores three Arabic medical text preprocessing techniques: text summarization, text refinement, and Named Entity Recognition (NER). |
Malak Mohamed; Rokaia Emad; Ali Hamdi; | arxiv-cs.CL | 2025-01-30 |
| 598 | OT-Transformer: A Continuous-time Transformer Architecture with Optimal Transport Regularization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a continuous-time formulation of transformers. |
Kelvin Kan; Xingjian Li; Stanley Osher; | arxiv-cs.LG | 2025-01-30 |
| 599 | Economic Rationality Under Specialization: Evidence of Decision Bias in AI Agents Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In the study by Chen et al. (2023) [01], the large language model GPT demonstrated economic rationality comparable to or exceeding the average human level in tasks such as budget allocation and risk preference. |
ShuiDe Wen; | arxiv-cs.AI | 2025-01-30 |
| 600 | Large Language Models Think Too Fast To Explore Effectively Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This study investigates whether LLMs can surpass humans in exploration during an open-ended task, using Little Alchemy 2 as a paradigm, where agents combine elements to discover new ones. |
Lan Pan; Hanbo Xie; Robert C. Wilson; | arxiv-cs.AI | 2025-01-29 |
| 601 | Towards Supporting Penetration Testing Education with Large Language Models: An Evaluation and Comparison Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study evaluates the effectiveness of LLMs in conducting a variety of penetration testing tasks. |
Martin Nizon-Deladoeuille; Brynjólfur Stefánsson; Helmut Neukirchen; Thomas Welsh; | arxiv-cs.CR | 2025-01-29 |
| 602 | DINT Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, it has two critical limitations: the lack of global context modeling, which is essential for identifying globally significant tokens, and numerical instability due to the absence of strict row normalization in the attention matrix. To overcome these challenges, we propose DINT Transformer, which extends DIFF Transformer by incorporating a differential-integral mechanism. |
Yueyang Cang; Yuhang Liu; Xiaoteng Zhang; Erlu Zhao; Li Shi; | arxiv-cs.CL | 2025-01-29 |
| 603 | Cross-Language Approach for Quranic QA Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, these systems face unique challenges, including the linguistic disparity between questions written in Modern Standard Arabic and answers found in Quranic verses written in Classical Arabic, and the small size of existing datasets, which further restricts model performance. To address these challenges, we adopt a cross-language approach by (1) Dataset Augmentation: expanding and enriching the dataset through machine translation to convert Arabic questions into English, paraphrasing questions to create linguistic diversity, and retrieving answers from an English translation of the Quran to align with multilingual training requirements; and (2) Language Model Fine-Tuning: utilizing pre-trained models such as BERT-Medium, RoBERTa-Base, DeBERTa-v3-Base, ELECTRA-Large, Flan-T5, Bloom, and Falcon to address the specific requirements of Quranic QA. |
Islam Oshallah; Mohamed Basem; Ali Hamdi; Ammar Mohammed; | arxiv-cs.CL | 2025-01-29 |
| 604 | AlphaAdam:Asynchronous Masked Optimization with Dynamic Alpha for Selective Updates Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose AlphaAdam, an optimization framework for LLM from the perspective of intra-layer parameter updates. |
Da Chang; Yu Li; Ganzhao Yuan; | arxiv-cs.LG | 2025-01-29 |
| 605 | Shared DIFF Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose Shared DIFF Transformer, which draws on the idea of a differential amplifier by introducing a shared base matrix to model global patterns and incorporating low-rank updates to enhance task-specific flexibility. |
Yueyang Cang; Yuhang Liu; Xiaoteng Zhang; Xiangju Wang; | arxiv-cs.LG | 2025-01-29 |
| 606 | Divergent Emotional Patterns in Disinformation on Social Media? An Analysis of Tweets and TikToks About The DANA in Valencia Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study investigates the dissemination of disinformation on social media platforms during the DANA event (DANA is a Spanish acronym for Depresion Aislada en Niveles Altos, translating to high-altitude isolated depression) that resulted in extremely heavy rainfall and devastating floods in Valencia, Spain, on October 29, 2024. |
Iván Arcos; Paolo Rosso; Ramón Salaverría; | arxiv-cs.CL | 2025-01-28 |
| 607 | Comparing Human and LLM Generated Code: The Jury Is Still Out! Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, there has been limited evaluation effort in the research domain aimed at validating the true utility of such techniques, especially when compared to human coding outputs. We bridge this gap, where a benchmark dataset comprising 72 distinct software engineering tasks is used to compare the effectiveness of large language models (LLMs) and human programmers in producing Python software code. |
Sherlock A. Licorish; Ansh Bajpai; Chetan Arora; Fanyu Wang; Kla Tantithamthavorn; | arxiv-cs.SE | 2025-01-28 |
| 608 | Detecting Harassment and Defamation in Cyberbullying with Emotion-adaptive Training Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, their performance is substantially lower on harassment and denigration multi-classification tasks. Therefore, we propose an emotion-adaptive training framework (EAT) that helps transfer knowledge from the domain of emotion detection to the domain of cyberbullying detection to help detect indirect cyberbullying events. |
Peiling Yi; Arkaitz Zubiaga; Yunfei Long; | arxiv-cs.CL | 2025-01-28 |
| 609 | MIDI-GPT: A Controllable Generative Model for Computer-Assisted Multitrack Music Composition Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present and release MIDI-GPT, a generative system based on the Transformer architecture that is designed for computer-assisted music composition workflows. |
PHILIPPE PASQUIER et. al. | arxiv-cs.SD | 2025-01-28 |
| 610 | Leveraging In-Context Learning and Retrieval-Augmented Generation for Automatic Question Generation in Educational Domains Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we explore advanced techniques for automated question generation in educational contexts, focusing on In-Context Learning (ICL), Retrieval-Augmented Generation (RAG), and a novel Hybrid Model that merges both methods. |
Subhankar Maity; Aniket Deroy; Sudeshna Sarkar; | arxiv-cs.CL | 2025-01-28 |
| 611 | MEL: Legal Spanish Language Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents the development and evaluation of MEL, a legal language model based on XLM-RoBERTa-large, fine-tuned on legal documents such as BOE (Bolet\’in Oficial del Estado, the Spanish oficial report of laws) and congress texts. |
DAVID BETANCUR SÁNCHEZ et. al. | arxiv-cs.CL | 2025-01-27 |
| 612 | Optimizing Sentence Embedding with Pseudo-Labeling and Model Ensembles: A Hierarchical Framework for Enhanced NLP Tasks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a framework that combines pseudo-label generation and model ensemble techniques to improve sentence embeddings. |
Ziwei Liu; Qi Zhang; Lifu Gao; | arxiv-cs.CL | 2025-01-27 |
| 613 | Optimizing Deep Learning Models to Address Class Imbalance in Code Comment Classification Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This work investigates the use of different weighting strategies of the loss function to mitigate the scarcity of certain classes in the dataset. |
Moritz Mock; Thomas Borsani; Giuseppe Di Fatta; Barbara Russo; | arxiv-cs.SE | 2025-01-27 |
| 614 | A Comprehensive Study on Fine-Tuning Large Language Models for Medical Question Answering Using Classification Models and Comparative Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents the overview of the development and fine-tuning of large language models (LLMs) designed specifically for answering medical questions. |
Aysegul Ucar; Soumik Nayak; Anunak Roy; Burak Taşcı; Gülay Taşcı; | arxiv-cs.CL | 2025-01-26 |
| 615 | Identifying Critical Tokens for Accurate Predictions in Transformer-based Medical Imaging Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we take a step towards demystifying the decision-making process of transformer-based medical imaging models and propose Token Insight, a novel method that identifies the critical tokens that contribute to the prediction made by the model. |
Solha Kang; Joris Vankerschaver; Utku Ozbulak; | arxiv-cs.CV | 2025-01-26 |
| 616 | TractoGPT: A GPT Architecture for White Matter Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: White Matter Segmentation remains challenging due to structural similarity in streamlines, subject variability, symmetry in 2 hemispheres, etc. To address these challenges, we propose TractoGPT, a GPT-based architecture trained on streamline, cluster, and fusion data representations separately. |
ANOUSHKRIT GOEL et. al. | arxiv-cs.CV | 2025-01-26 |
| 617 | Evaluating Simple Debiasing Techniques in RoBERTa-based Hate Speech Detection Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This leads to a disparity where normal AAE text is more likely to be misclassified as abusive/hateful compared to non-AAE text. Simple debiasing techniques have been developed in the past to counter this sort of disparity, and in this work, we apply and evaluate these techniques in the scope of RoBERTa-based encoders. |
Diana Iftimie; Erik Zinn; | arxiv-cs.CL | 2025-01-26 |
| 618 | Multi-stage Large Language Model Pipelines Can Outperform GPT-4o in Relevance Assessment Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose an LLM-based modular classification pipeline that divides the relevance assessment task into multiple stages, each utilising different prompts and models of varying sizes and capabilities. |
Julian A. Schnabel; Johanne R. Trippas; Falk Scholer; Danula Hettiachchi; | arxiv-cs.IR | 2025-01-24 |
| 619 | An Empirical Study on LLM-based Classification of Requirements-related Provisions in Food-safety Regulations Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this article, we pursue two main goals. |
Shabnam Hassani; Mehrdad Sabetzadeh; Daniel Amyot; | arxiv-cs.SE | 2025-01-24 |
| 620 | Idiom Detection in Sorani Kurdish Texts Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This research provides a dataset, three optimized models, and insights into idiom detection, laying a foundation for advancing Kurdish NLP. |
Skala Kamaran Omer; Hossein Hassani; | arxiv-cs.CL | 2025-01-24 |
| 621 | Assessing Large Language Models in Comprehending and Verifying Concurrent Programs Across Memory Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study evaluates the performance of several leading large language models (LLMs), including GPT-3.5-turbo, GPT-4, GPT-4o, GPT-4o-mini, and Mistral-AI’s Large2, in understanding and analyzing concurrency issues within software programs. |
Ridhi Jain; Rahul Purandare; | arxiv-cs.SE | 2025-01-24 |
| 622 | Prompt-Based Cost-Effective Evaluation and Operation of ChatGPT As A Computer Programming Teaching Assistant Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: One potential application of these models in the educational field would be to provide feedback to students in university introductory programming courses, so that a student struggling to solve a basic implementation problem could seek help from an LLM available 24/7. This article focuses on studying three aspects related to such an application. |
Marc Ballestero-Ribó; Daniel Ortiz-Martínez; | arxiv-cs.CY | 2025-01-24 |
| 623 | GPT-HTree: A Decision Tree Framework Integrating Hierarchical Clustering and Large Language Models for Explainable Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces GPT-HTree, a framework combining hierarchical clustering, decision trees, and large language models (LLMs) to address this challenge. |
Te Pei; Fuat Alican; Aaron Ontoyin Yin; Yigit Ihlamur; | arxiv-cs.LG | 2025-01-23 |
| 624 | A Transformer-based Autoregressive Decoder Architecture for Hierarchical Text Classification Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce an effective hierarchical text classifier RADAr (Transformer-based Autoregressive Decoder Architecture) that is based only on an off-the-shelf RoBERTa transformer to process the input and a custom autoregressive decoder with two decoder layers for generating the classification output. |
Younes Yousef; Lukas Galke; Ansgar Scherp; | arxiv-cs.LG | 2025-01-23 |
| 625 | Multi-Level Attention and Contrastive Learning for Enhanced Text Classification with An Optimized Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The method proposed in this paper provides a new idea for algorithm optimization in the field of text classification and has good application potential and practical value. |
JIA GAO et. al. | arxiv-cs.CL | 2025-01-23 |
| 626 | Question Answering on Patient Medical Records with Private Fine-Tuned LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, ensuring privacy and compliance requires edge and private deployments of LLMs. This paper proposes a novel approach to semantic QA over EHRs by first identifying the most relevant FHIR resources for a user query (Task1) and subsequently answering the query based on these resources (Task2). |
Sara Kothari; Ayush Gupta; | arxiv-cs.CL | 2025-01-23 |
| 627 | Quantized Spike-driven Transformer Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, recent research in the SNN domain has mainly focused on enhancing accuracy by designing large-scale Transformer structures, which typically rely on substantial computational resources, limiting their deployment on resource-constrained devices. To overcome this challenge, we propose a quantized spike-driven Transformer baseline (QSD-Transformer), which achieves reduced resource demands by utilizing a low bit-width parameter. |
XUERUI QIU et. al. | arxiv-cs.CV | 2025-01-23 |
| 628 | 5G LDPC Linear Transformer for Channel Decoding Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a scalable approach to decode linear block codes with $O(n)$ complexity rather than $O(n^2)$ for regular transformers. |
Mario Hernandez; Fernando Pinero; | arxiv-cs.LG | 2025-01-23 |
| 629 | MedSlice: Fine-Tuned Large Language Models for Secure Clinical Note Sectioning Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This study develops a pipeline for automated note sectioning using open-source LLMs, focusing on three sections: History of Present Illness, Interval History, and Assessment and Plan. |
JOSHUA DAVIS et. al. | arxiv-cs.CL | 2025-01-23 |
| 630 | LiT: Delving Into A Simplified Linear Diffusion Transformer for Image Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we offer a suite of ready-to-use solutions for efficient linear diffusion Transformers. |
JIAHAO WANG et. al. | arxiv-cs.CV | 2025-01-22 |
| 631 | LuxVeri at GenAI Detection Task 3: Cross-Domain Detection of AI-Generated Text Using Inverse Perplexity-Weighted Ensemble of Fine-Tuned Transformer Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents our approach for Task 3 of the GenAI content detection workshop at COLING-2025, focusing on Cross-Domain Machine-Generated Text (MGT) Detection. |
Md Kamrujjaman Mobin; Md Saiful Islam; | arxiv-cs.CL | 2025-01-21 |
| 632 | Harnessing Generative Pre-Trained Transformer for Datacenter Packet Trace Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Researchers often use simplified mathematical models that lack the depth needed to recreate intricate traffic patterns and, thus, miss optimization opportunities found in realistic traffic. In this preliminary work, we introduce DTG-GPT, a packet-level Datacenter Traffic Generator (DTG), based on the generative pre-trained transformer (GPT) architecture used by many state-of-the-art large language models. |
Chen Griner; | arxiv-cs.NI | 2025-01-21 |
| 633 | Vision-Language Models for Automated Chest X-ray Interpretation: Leveraging ViT and GPT-2 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study we have evaluated different combinations of multimodal models that integrate Computer Vision and Natural Language Processing to generate comprehensive radiology reports. |
Md. Rakibul Islam; Md. Zahid Hossain; Mustofa Ahmed; Most. Sharmin Sultana Samu; | arxiv-cs.CV | 2025-01-21 |
| 634 | Comparative Approaches to Sentiment Analysis Using Datasets in Major European and Arabic Languages Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study explores transformer-based models such as BERT, mBERT, and XLM-R for multi-lingual sentiment analysis across diverse linguistic structures. |
Mikhail Krasitskii; Olga Kolesnikova; Liliana Chanona Hernandez; Grigori Sidorov; Alexander Gelbukh; | arxiv-cs.CL | 2025-01-21 |
| 635 | FuocChuVIP123 at CoMeDi Shared Task: Disagreement Ranking with XLM-Roberta Sentence Embeddings and Deep Neural Regression Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents results of our system for CoMeDi Shared Task, focusing on Subtask 2: Disagreement Ranking. |
Phuoc Duong Huy Chu; | arxiv-cs.CL | 2025-01-21 |
| 636 | LuxVeri at GenAI Detection Task 1: Inverse Perplexity Weighted Ensemble for Robust Detection of AI-Generated Text Across English and Multilingual Contexts Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a system developed for Task 1 of the COLING 2025 Workshop on Detecting AI-Generated Content, focusing on the binary classification of machine-generated versus human-written text. |
Md Kamrujjaman Mobin; Md Saiful Islam; | arxiv-cs.CL | 2025-01-21 |
| 637 | Evaluating Binary Decision Biases in Large Language Models: Implications for Fair Agent-Based Financial Simulations Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Large Language Models (LLMs) are increasingly being used to simulate human-like decision making in agent-based financial market models (ABMs). As models become more powerful and … |
Alicia Vidler; Toby Walsh; | ArXiv | 2025-01-20 |
| 638 | KEIR @ ECIR 2025: The Second Workshop on Knowledge-Enhanced Information Retrieval Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The goal of this workshop is to bring together researchers from academia and industry to discuss various aspects of knowledge-enhanced information retrieval. |
ZIHAN WANG et. al. | arxiv-cs.IR | 2025-01-20 |
| 639 | Trustformer: A Trusted Federated Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces a novel FL method that reduces communication overhead while maintaining competitive utility. |
Ali Abbasi Tadi; Dima Alhadidi; Luis Rueda; | arxiv-cs.LG | 2025-01-20 |
| 640 | Irony in Emojis: A Comparative Study of Human and LLM Interpretation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study examines the ability of GPT-4o to interpret irony in emojis. By prompting GPT-4o to evaluate the likelihood of specific emojis being used to express irony on social media and comparing its interpretations with human perceptions, we aim to bridge the gap between machine and human understanding. |
Yawen Zheng; Hanjia Lyu; Jiebo Luo; | arxiv-cs.CL | 2025-01-19 |
| 641 | PaSa: An LLM Agent for Comprehensive Academic Paper Search 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. | arxiv-cs.IR | 2025-01-17 |
| 642 | Improving Automated Feedback Systems for Tutor Training in Low-Resource Scenarios Through Data Augmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Our results demonstrate that our data augmentation approach generalizes effectively to identify other types of praise, compared to the same model fine-tuned without augmentation. |
Chentianye Xu; Jionghao Lin; Tongshuang Wu; Vincent Aleven; Kenneth R. Koedinger; | arxiv-cs.HC | 2025-01-16 |
| 643 | Demo: Interactive Visualization of Semantic Relationships in A Biomedical Project’s Talent Knowledge Graph Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present an interactive visualization of the Cell Map for AI Talent Knowledge Graph (CM4AI TKG), a detailed semantic space comprising approximately 28,000 experts and 1,000 datasets focused on the biomedical field. |
JIAWEI XU et. al. | arxiv-cs.SI | 2025-01-16 |
| 644 | Exploring ChatGPT for Face Presentation Attack Detection in Zero and Few-Shot In-Context Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study highlights the potential of ChatGPT (specifically GPT-4o) as a competitive alternative for Face Presentation Attack Detection (PAD), outperforming several PAD models, including commercial solutions, in specific scenarios. |
Alain Komaty; Hatef Otroshi Shahreza; Anjith George; Sebastien Marcel; | arxiv-cs.CV | 2025-01-15 |
| 645 | Expanding Vietnamese SentiWordNet to Improve Performance of Vietnamese Sentiment Analysis Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce a novel approach that combines PhoBERT-V2 and SentiWordnet for Sentiment Analysis of Vietnamese reviews. |
Hong-Viet Tran; Van-Tan Bui; Lam-Quan Tran; | arxiv-cs.CL | 2025-01-15 |
| 646 | Towards Multilingual LLM Evaluation for Baltic and Nordic Languages: A Study on Lithuanian History Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we evaluated Lithuanian and general history knowledge of multilingual Large Language Models (LLMs) on a multiple-choice question-answering task. |
Yevhen Kostiuk; Oxana Vitman; Łukasz Gagała; Artur Kiulian; | arxiv-cs.CL | 2025-01-15 |
| 647 | Enhancing The De-identification of Personally Identifiable Information in Educational Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Motivated by recent advancements in artificial intelligence, our study investigates the GPT-4o-mini model as a cost-effective and efficient solution for PII detection tasks. |
Y. Shen; Z. Ji; J. Lin; K. R. Koedginer; | arxiv-cs.CL | 2025-01-14 |
| 648 | Tarsier2: Advancing Large Vision-Language Models from Detailed Video Description to Comprehensive Video Understanding Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce Tarsier2, a state-of-the-art large vision-language model (LVLM) designed for generating detailed and accurate video descriptions, while also exhibiting superior general video understanding capabilities. |
Liping Yuan; Jiawei Wang; Haomiao Sun; Yuchen Zhang; Yuan Lin; | arxiv-cs.CV | 2025-01-14 |
| 649 | Comparative Analysis of Efficient Adapter-Based Fine-Tuning of State-of-the-Art Transformer Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we investigate the efficacy of various adapter architectures on supervised binary classification tasks from the SuperGLUE benchmark as well as a supervised multi-class news category classification task from Kaggle. |
Saad Mashkoor Siddiqui; Mohammad Ali Sheikh; Muhammad Aleem; Kajol R Singh; | arxiv-cs.CL | 2025-01-14 |
| 650 | Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Using a dataset of narratives developed via GPT-4, featuring diverse semantic content and stylistic variations, we analyze BERT’s layerwise activations to uncover patterns of localized neural processing. Through dimensionality reduction techniques such as Principal Component Analysis (PCA) and Multidimensional Scaling (MDS), we reveal that BERT exhibits strong clustering based on narrative content in its later layers, with progressively compact and distinct clusters. |
Awritrojit Banerjee; Achim Schilling; Patrick Krauss; | arxiv-cs.CL | 2025-01-14 |
| 651 | GPT As A Monte Carlo Language Tree: A Probabilistic Perspective Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel perspective that any language dataset can be represented by a Monte Carlo Language Tree (abbreviated as “Data-Tree”), where each node denotes a token, each edge denotes a token transition probability, and each sequence has a unique path. |
Kun-Peng Ning; Jia-Yu Yao; Yu-Yang Liu; Mu-Nan Ning; Li Yuan; | arxiv-cs.CL | 2025-01-13 |
| 652 | An Efficient Sparse Hardware Accelerator for Spike-Driven Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose an efficient sparse hardware accelerator for Spike-driven Transformer. |
Zhengke Li; Wendong Mao; Siyu Zhang; Qiwei Dong; Zhongfeng Wang; | arxiv-cs.AR | 2025-01-13 |
| 653 | Investigating Large Language Models in Inferring Personality Traits from User Conversations Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Large Language Models (LLMs) are demonstrating remarkable human like capabilities across diverse domains, including psychological assessment. |
Jianfeng Zhu; Ruoming Jin; Karin G. Coifman; | arxiv-cs.CL | 2025-01-13 |
| 654 | Transforming Role Classification in Scientific Teams Using LLMs and Advanced Predictive Analytics Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Thus, we present a transformative approach to classifying author roles in scientific teams using advanced large language models (LLMs), which offers a more refined analysis compared to traditional clustering methods. |
Wonduk Seo; Yi Bu; | arxiv-cs.DL | 2025-01-13 |
| 655 | Robust Hybrid Classical-Quantum Transfer Learning Model for Text Classification Using GPT-Neo 125M with LoRA & SMOTE Enhancement Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This research introduces a hybrid classical-quantum framework for text classification, integrating GPT-Neo 125M with Low-Rank Adaptation (LoRA) and Synthetic Minority Over-sampling Technique (SMOTE) using quantum computing backends. |
Santanam Wishal; | arxiv-cs.LG | 2025-01-12 |
| 656 | Generative Artificial Intelligence-Supported Pentesting: A Comparison Between Claude Opus, GPT-4, and Copilot Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we have analyzed the potential of leading generic-purpose GenAI tools-Claude Opus, GPT-4 from ChatGPT, and Copilot-in augmenting the penetration testing process as defined by the Penetration Testing Execution Standard (PTES). |
Antonio López Martínez; Alejandro Cano; Antonio Ruiz-Martínez; | arxiv-cs.CR | 2025-01-12 |
| 657 | Assessing Instructor-AI Cooperation for Grading Essay-type Questions in An Introductory Sociology Course Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This study explores the use of artificial intelligence (AI) as a complementary tool for grading essay-type questions in higher education, focusing on its consistency with human grading and potential to reduce biases. |
Francisco Olivos; Tobias Kamelski; Sebastián Ascui-Gac; | arxiv-cs.AI | 2025-01-11 |
| 658 | Comparing Few-Shot Prompting of GPT-4 LLMs with BERT Classifiers for Open-Response Assessment in Tutor Equity Training Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Here, we study whether fine-tuning BERT on human annotations outperforms state-of-the-art LLMs (GPT-4o and GPT-4-Turbo) with few-shot prompting and instruction. |
Sanjit Kakarla; Conrad Borchers; Danielle Thomas; Shambhavi Bhushan; Kenneth R. Koedinger; | arxiv-cs.HC | 2025-01-11 |
| 659 | ZNO-Eval: Benchmarking Reasoning Capabilities of Large Language Models in Ukrainian Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The purpose of this work is to establish a comprehensive benchmark for the reasoning capabilities evaluation of large language models in the Ukrainian language. |
Mykyta Syromiatnikov; Victoria Ruvinskaya; Anastasiya Troynina; | arxiv-cs.CL | 2025-01-11 |
| 660 | Model Inversion in Split Learning for Personalized LLMs: New Insights from Information Bottleneck Theory Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: For the first time, we introduce mutual information entropy to understand the information propagation of Transformer-based LLMs and assess privacy attack performance for LLM blocks. |
Yunmeng Shu; Shaofeng Li; Tian Dong; Yan Meng; Haojin Zhu; | arxiv-cs.LG | 2025-01-10 |
| 661 | Aligning Brain Activity with Advanced Transformer Models: Exploring The Role of Punctuation in Semantic Processing Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Utilizing an innovative approach originally proposed by Toneva and Wehbe, we evaluate four advanced transformer models RoBERTa, DistiliBERT, ALBERT, and ELECTRA against neural activity data. |
Zenon Lamprou; Frank Polick; Yashar Moshfeghi; | arxiv-cs.CL | 2025-01-10 |
| 662 | From Conversation to Automation: Leveraging LLMs for Problem-Solving Therapy Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We developed a comprehensive framework for PST annotation using established PST Core Strategies and a set of novel Facilitative Strategies to analyze a corpus of real-world therapy transcripts to determine which strategies are most prevalent. |
ELHAM AGHAKHANI et. al. | arxiv-cs.CL | 2025-01-10 |
| 663 | OpenAI ChatGPT Interprets Radiological Images: GPT-4 As A Medical Doctor for A Fast Check-Up Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this way, we addressed the question of whether artificial intelligence (AI) can replace a healthcare professional (e.g., a medical doctor) or whether it can be used as a decision-support tool that makes decisions easier and more reliable. |
Omer Aydin; Enis Karaarslan; | arxiv-cs.CV | 2025-01-09 |
| 664 | UAV-VLA: Vision-Language-Action System for Large Scale Aerial Mission Generation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The newly developed method showed the difference in the length of the created trajectory in 22% and the mean error in finding the objects of interest on a map in 34.22 m by Euclidean distance in the K-Nearest Neighbors (KNN) approach. |
OLEG SAUTENKOV et. al. | arxiv-cs.RO | 2025-01-09 |
| 665 | MB-TaylorFormer V2: Improved Multi-branch Linear Transformer Expanded By Taylor Formula for Image Restoration Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, the quadratic computational complexity of Softmax-attention poses a significant limitation on its extensive application in image restoration tasks, particularly for high-resolution images. To tackle this challenge, we propose a novel variant of the Transformer. |
Zhi Jin; Yuwei Qiu; Kaihao Zhang; Hongdong Li; Wenhan Luo; | arxiv-cs.CV | 2025-01-08 |
| 666 | A Case Study on The Transformative Potential of AI in Software Engineering on LeetCode and ChatGPT Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This contribution presents a first large-scale study comparing generated code with human-written code based on LeetCode platform based on multiple measures including code quality, code understandability, time behaviour and resource utilisation. |
Manuel Merkel; Jens Dörpinghaus; | arxiv-cs.DB | 2025-01-07 |
| 667 | IntegrityAI at GenAI Detection Task 2: Detecting Machine-Generated Academic Essays in English and Arabic Using ELECTRA and Stylometry Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Recent research has investigated the problem of detecting machine-generated essays for academic purposes. |
Mohammad AL-Smadi; | arxiv-cs.CL | 2025-01-07 |
| 668 | Three-dimensional Attention Transformer for State Evaluation in Real-time Strategy Games Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Here we propose a tri-dimensional Space-Time-Feature Transformer (TSTF Transformer) architecture, which efficiently models battlefield situations through three independent but cascaded modules: spatial attention, temporal attention, and feature attention. |
Yanqing Ye; Weilong Yang; Kai Qiu; Jie Zhang; | arxiv-cs.LG | 2025-01-07 |
| 669 | Empowering Bengali Education with AI: Solving Bengali Math Word Problems Through Transformer Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This poses a significant challenge in natural language processing, particularly for low-resource languages such as Bengali. This paper addresses this challenge by developing an innovative approach to solving Bengali MWPs using transformer-based models, including Basic Transformer, mT5, BanglaT5, and mBART50. |
Jalisha Jashim Era; Bidyarthi Paul; Tahmid Sattar Aothoi; Mirazur Rahman Zim; Faisal Muhammad Shah; | arxiv-cs.CL | 2025-01-05 |
| 670 | LeetDecoding: A PyTorch Library for Exponentially Decaying Causal Linear Attention with CUDA Implementations Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The machine learning and data science community has made significant while dispersive progress in accelerating transformer-based large language models (LLMs), and one promising approach is to replace the original causal attention in a generative pre-trained transformer (GPT) with \emph{exponentially decaying causal linear attention}. In this paper, we present LeetDecoding, which is the first Python package that provides a large set of computation routines for this fundamental operator. |
Jiaping Wang; Simiao Zhang; Qiao-Chu He; Yifan Chen; | arxiv-cs.LG | 2025-01-05 |
| 671 | A Completely Uniform Transformer for Parity Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We construct a 3-layer constant-dimension transformer, recognizing the parity language, where neither parameter matrices nor the positional encoding depend on the input length. |
Alexander Kozachinskiy; Tomasz Steifer; | arxiv-cs.LG | 2025-01-05 |
| 672 | Sensorformer: Cross-patch Attention with Global-patch Compression Is Effective for High-dimensional Multivariate Time Series Forecasting Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We attribute this issue to the dynamic time lags in the causal relationships between different variables. Therefore, we propose a new multivariate time series forecasting Transformer, Sensorformer, which first compresses the global patch information and then simultaneously extracts cross-variable and cross-time dependencies from the compressed representations. |
Liyang Qin; Xiaoli Wang; Chunhua Yang; Huaiwen Zou; Haochuan Zhang; | arxiv-cs.LG | 2025-01-05 |
| 673 | LLMs & Legal Aid: Understanding Legal Needs Exhibited Through User Queries Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The paper presents a preliminary analysis of an experiment conducted by Frank Bold, a Czech expert group, to explore user interactions with GPT-4 for addressing legal queries. |
Michal Kuk; Jakub Harasta; | arxiv-cs.HC | 2025-01-03 |
| 674 | VidFormer: A Novel End-to-end Framework Fused By 3DCNN and Transformer for Video-based Remote Physiological Measurement Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce VidFormer, a novel end-to-end framework that integrates 3-Dimension Convolutional Neural Network (3DCNN) and Transformer models for rPPG tasks. |
JIACHEN LI et. al. | arxiv-cs.CV | 2025-01-03 |
| 675 | End-to-End Long Document Summarization Using Gradient Caching Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose CachED (Gradient$\textbf{Cach}$ing for $\textbf{E}$ncoder-$\textbf{D}$ecoder models), anapproach that enables end-to-end training of existing transformer-basedencoder-decoder models, using the entire document without truncation.Specifically, we apply non-overlapping sliding windows to input documents,followed by fusion in decoder. |
Rohit Saxena; Hao Tang; Frank Keller; | arxiv-cs.CL | 2025-01-03 |
| 676 | 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). |
LIXIONG QIN et. al. | arxiv-cs.CV | 2025-01-02 |
| 677 | Digital Guardians: Can GPT-4, Perspective API, and Moderation API Reliably Detect Hate Speech in Reader Comments of German Online Newspapers? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Some providers of large language models already offer solutions for automated hate speech detection or the identification of toxic content. |
MANUEL WEBER et. al. | arxiv-cs.CL | 2025-01-02 |
| 678 | Multi-Head Explainer: A General Framework to Improve Explainability in CNNs and Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we introduce the Multi-Head Explainer (MHEX), a versatile and modular framework that enhances both the explainability and accuracy of Convolutional Neural Networks (CNNs) and Transformer-based models. |
Bohang Sun; Pietro Liò; | arxiv-cs.CV | 2025-01-02 |
| 679 | Predicting The Performance of Black-box LLMs Through Self-Queries Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we extract features of LLMs in a black-box manner by using follow-up prompts and taking the probabilities of different responses as representations to train reliable predictors of model behavior. |
Dylan Sam; Marc Finzi; J. Zico Kolter; | arxiv-cs.LG | 2025-01-02 |
| 680 | An Efficient Attention Mechanism for Sequential Recommendation Tasks: HydraRec Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Building on the idea of Hydra attention, we introduce an efficient Transformer based Sequential RS (HydraRec) which significantly improves theoretical complexity of computing attention for longer sequences and bigger datasets while preserving the temporal context. |
Uzma Mushtaque; | arxiv-cs.IR | 2025-01-02 |
| 681 | Multiscaled Multi-Head Attention-based Video Transformer Network for Hand Gesture Recognition IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this letter, Multiscaled Multi-Head Attention Video Transformer Network (MsMHA-VTN) for dynamic hand gesture recognition is proposed. |
Mallika Garg; Debashis Ghosh; Pyari Mohan Pradhan; | arxiv-cs.CV | 2025-01-01 |
| 682 | Aircraft Trajectory Prediction With Inverted Transformer Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Aircraft trajectory prediction plays a crucial role in air traffic management and significantly enhances operational safety and efficiency. In this work, we propose an aircraft … |
S. Yoon; Keumjin Lee; | IEEE Access | 2025-01-01 |
| 683 | Hadamard Attention Recurrent Transformer: A Strong Baseline for Stereo Matching Transformer Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: Constrained by the low-rank bottleneck inherent in attention mechanisms,current stereo matching transformers suffer from limited nonlinearexpressivity, which renders their feature … |
ZIYANG CHEN et. al. | arxiv-cs.CV | 2025-01-01 |
| 684 | Sequential Recommendation By Reprogramming Pretrained Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View |
MIN TANG et. al. | Inf. Process. Manag. | 2025-01-01 |
| 685 | Why Are Positional Encodings Nonessential for Deep Autoregressive Transformers? Revisiting A Petroglyph Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This may be partially due to a sudden growth of the language modeling community after the advent of GPT-2/3, but perhaps also due to the lack of a clear explanation in prior work, despite being commonly understood by practitioners in the past. Here we review the long-forgotten explanation why explicit PEs are nonessential for multi-layer autoregressive Transformers (in contrast, one-layer models require PEs to discern order information of their inputs), as well as the origin of this result, and hope to re-establish it as a common knowledge. |
Kazuki Irie; | arxiv-cs.LG | 2024-12-31 |
| 686 | ReFormer: Generating Radio Fakes for Data Augmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present ReFormer, a generative AI (GAI) model that can efficiently generate synthetic radio-frequency (RF) data, or RF fakes, statistically similar to the data it was trained on, or with modified statistics, in order to augment datasets collected in real-world experiments. |
Yagna Kaasaragadda; Silvija Kokalj-Filipovic; | arxiv-cs.LG | 2024-12-31 |
| 687 | Text Classification: Neural Networks VS Machine Learning Models VS Pre-trained Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we present a comparison between different techniques to perform text classification. |
Christos Petridis; | arxiv-cs.LG | 2024-12-30 |
| 688 | GPT-4 on Clinic Depression Assessment: An LLM-Based Pilot Study Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we explore the use of GPT-4 for clinical depression assessment based on transcript analysis. |
Giuliano Lorenzoni; Pedro Elkind Velmovitsky; Paulo Alencar; Donald Cowan; | arxiv-cs.CL | 2024-12-30 |
| 689 | On Adversarial Robustness of Language Models in Transfer Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We investigate the adversarial robustness of LLMs in transfer learning scenarios. |
Bohdan Turbal; Anastasiia Mazur; Jiaxu Zhao; Mykola Pechenizkiy; | arxiv-cs.CL | 2024-12-29 |
| 690 | ELECTRA and GPT-4o: Cost-Effective Partners for Sentiment Analysis Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper explores collaborative approaches between ELECTRA and GPT-4o for three-way sentiment classification. |
James P. Beno; | arxiv-cs.CL | 2024-12-29 |
| 691 | Comparative Performance of Advanced NLP Models and LLMs in Multilingual Geo-Entity Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a comprehensive evaluation of leading NLP models — SpaCy, XLM-RoBERTa, mLUKE, GeoLM — and LLMs, specifically OpenAI’s GPT 3.5 and GPT 4, within the context of multilingual geo-entity detection. |
Kalin Kopanov; | arxiv-cs.CL | 2024-12-29 |
| 692 | NLP-based Regulatory Compliance — Using GPT 4.0 to Decode Regulatory Documents Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Large Language Models (LLMs) such as GPT-4.0 have shown significant promise in addressing the semantic complexities of regulatory documents, particularly in detecting inconsistencies and contradictions. |
Bimal Kumar; Dmitri Roussinov; | arxiv-cs.CL | 2024-12-29 |
| 693 | Building A Rich Dataset to Empower The Persian Question Answering Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, a comprehensive open-domain dataset is presented for Persian. |
Mohsen Yazdinejad; Marjan Kaedi; | arxiv-cs.CL | 2024-12-28 |
| 694 | Distilled Transformers with Locally Enhanced Global Representations for Face Forgery Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a distilled transformer network (DTN) to capture both rich local and global forgery traces and learn general and common representations for different forgery faces. |
Yaning Zhang; Qiufu Li; Zitong Yu; Linlin Shen; | arxiv-cs.CV | 2024-12-28 |
| 695 | Generative Pretrained Embedding and Hierarchical Irregular Time Series Representation for Daily Living Activity Recognition Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To further refine recognition, we incorporate into our proposed architecture an hour-of-the-day embedding. |
Damien Bouchabou; Sao Mai Nguyen; | arxiv-cs.LG | 2024-12-27 |
| 696 | Assessing Text Classification Methods for Cyberbullying Detection on Social Media Platforms Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This research aims to conduct a comparative study by adapting and evaluating existing text classification techniques within the cyberbullying detection domain. |
Adamu Gaston Philipo; Doreen Sebastian Sarwatt; Jianguo Ding; Mahmoud Daneshmand; Huansheng Ning; | arxiv-cs.CL | 2024-12-27 |
| 697 | DrivingWorld: Constructing World Model for Autonomous Driving Via Video GPT Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present DrivingWorld, a GPT-style world model for autonomous driving, featuring several spatial-temporal fusion mechanisms. |
XIAOTAO HU et. al. | arxiv-cs.CV | 2024-12-27 |
| 698 | Feature Alignment-Based Knowledge Distillation for Efficient Compression of Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study proposes a knowledge distillation algorithm based on large language models and feature alignment, aiming to effectively transfer the knowledge of large pre-trained models into lightweight student models, thereby reducing computational costs while maintaining high model performance. |
SHUO WANG et. al. | arxiv-cs.CL | 2024-12-26 |
| 699 | LoGFiLM: Fine-Tuning A Large Language Model for Automated Generation of Log Statements Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Fine-tuning LLMs requires task-specific training data and custom-designed processing algorithms, which, however, have not been thoroughly explored for the log statement generation task. This paper fills this gap by contributing such a fine-tuning method LoGFiLM and an exemplar model by using the proposed method to fine-tune Llama-3-8B. |
HAO ZHANG et. al. | arxiv-cs.SE | 2024-12-25 |
| 700 | Injecting Bias Into Text Classification Models Using Backdoor Attacks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose to utilize backdoor attacks for a new purpose: bias injection. |
A. Dilara Yavuz; M. Emre Gursoy; | arxiv-cs.CR | 2024-12-25 |
| 701 | Open-Vocabulary Panoptic Segmentation Using BERT Pre-Training of Vision-Language Multiway Transformer Model Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose OMTSeg for open-vocabulary segmentation using another large-scale vision-language pre-trained model called BEiT-3 and leveraging the cross-modal attention between visual and linguistic features in BEiT-3 to achieve better performance. |
Yi-Chia Chen; Wei-Hua Li; Chu-Song Chen; | arxiv-cs.CV | 2024-12-25 |
| 702 | Whose Morality Do They Speak? Unraveling Cultural Bias in Multilingual Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study investigates whether multilingual LLMs, such as GPT-3.5-Turbo, GPT-4o-mini, Llama 3.1, and MistralNeMo, reflect culturally specific moral values or impose dominant moral norms, particularly those rooted in English. |
Meltem Aksoy; | arxiv-cs.CL | 2024-12-25 |
| 703 | Ister: Inverted Seasonal-Trend Decomposition Transformer for Explainable Multivariate Time Series Forecasting Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, existing models face challenges in identifying critical components for prediction, leading to limited interpretability and suboptimal performance. To address these issues, we propose the Inverted Seasonal-Trend Decomposition Transformer (Ister), a novel Transformer-based model for multivariate time series forecasting. |
Fanpu Cao; Shu Yang; Zhengjian Chen; Ye Liu; Laizhong Cui; | arxiv-cs.LG | 2024-12-25 |
| 704 | 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; | arxiv-cs.CL | 2024-12-24 |
| 705 | Combining GPT and Code-Based Similarity Checking for Effective Smart Contract Vulnerability Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present SimilarGPT, a unique vulnerability identification tool for smart contract, which combines Generative Pretrained Transformer (GPT) models with Code-based similarity checking methods. |
Jango Zhang; | arxiv-cs.SE | 2024-12-24 |
| 706 | Optimizing Large Language Models with An Enhanced LoRA Fine-Tuning Algorithm for Efficiency and Robustness in NLP Tasks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study proposes a large language model optimization method based on the improved LoRA fine-tuning algorithm, aiming to improve the accuracy and computational efficiency of the model in natural language processing tasks. |
JIACHENG HU et. al. | arxiv-cs.CL | 2024-12-24 |
| 707 | Unlocking The Potential of Multiple BERT Models for Bangla Question Answering in NCTB Textbooks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study investigates the capability of state-of-the-art language models-RoBERTa Base, Bangla-BERT, and BERT Base-in automatically assessing Bangla passage-based question-answering from the National Curriculum and Textbook Board (NCTB) textbooks for classes 6-10. |
Abdullah Khondoker; Enam Ahmed Taufik; Md Iftekhar Islam Tashik; S M Ishtiak mahmud; Antara Firoz Parsa; | arxiv-cs.CL | 2024-12-24 |
| 708 | IITR-CIOL@NLU of Devanagari Script Languages 2025: Multilingual Hate Speech Detection and Target Identification in Devanagari-Scripted Languages Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose the MultilingualRobertaClass model, a deep neural network built on the pretrained multilingual transformer model ia-multilingual-transliterated-roberta, optimized for classification tasks in multilingual and transliterated contexts. |
Siddhant Gupta; Siddh Singhal; Azmine Toushik Wasi; | arxiv-cs.CL | 2024-12-23 |
| 709 | 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. | arxiv-cs.LG | 2024-12-23 |
| 710 | SubstationAI: Multimodal Large Model-Based Approaches for Analyzing Substation Equipment Faults Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes a substation equipment fault analysis method based on a multimodal large language model (MLLM). |
JINZHI WANG et. al. | arxiv-cs.AI | 2024-12-22 |
| 711 | PsychAdapter: Adapting LLM Transformers to Reflect Traits, Personality and Mental Health Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Here, we propose a lightweight modification to the standard language model transformer architecture – PsychAdapter – that uses empirically derived trait-language patterns to generate natural language for specified personality, demographic, and mental health characteristics (with or without prompting). |
HUY VU et. al. | arxiv-cs.AI | 2024-12-22 |
| 712 | 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 (VQ-VAE) and a Generative Pre-trained Transformer (GPT) to generate high-quality 3D assets. |
XUYING ZHANG et. al. | arxiv-cs.CV | 2024-12-22 |
| 713 | Development of A Large-scale Dataset of Chest Computed Tomography Reports in Japanese and A High-performance Finding Classification Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Objective: To develop a comprehensive Japanese CT report dataset through machine translation and establish a specialized language model for structured finding classification. |
YOSUKE YAMAGISHI et. al. | arxiv-cs.CL | 2024-12-20 |
| 714 | BabyHGRN: Exploring RNNs for Sample-Efficient Training of Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper explores the potential of recurrent neural networks (RNNs) and other subquadratic architectures as competitive alternatives to transformer-based models in low-resource language modeling scenarios. |
Patrick Haller; Jonas Golde; Alan Akbik; | arxiv-cs.CL | 2024-12-20 |
| 715 | Demystifying The Potential of ChatGPT-4 Vision for Construction Progress Monitoring Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The integration of Large Vision-Language Models (LVLMs) such as OpenAI’s GPT-4 Vision into various sectors has marked a significant evolution in the field of artificial intelligence, particularly in the analysis and interpretation of visual data. This paper explores the practical application of GPT-4 Vision in the construction industry, focusing on its capabilities in monitoring and tracking the progress of construction projects. |
Ahmet Bahaddin Ersoz; | arxiv-cs.CV | 2024-12-20 |
| 716 | Linguistic Features Extracted By GPT-4 Improve Alzheimer’s Disease Detection Based on Spontaneous Speech Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this study, we leverage GPT-4 to extract five semantic features from transcripts of spontaneous patient speech. |
Jonathan Heitz; Gerold Schneider; Nicolas Langer; | arxiv-cs.CL | 2024-12-20 |
| 717 | Identifying Cyberbullying Roles in Social Media Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study explores the use of machine learning models to detect the roles involved in cyberbullying interactions. |
MANUEL SANDOVAL et. al. | arxiv-cs.LG | 2024-12-20 |
| 718 | Graph-Convolutional Networks: Named Entity Recognition and Large Language Model Embedding in Document Clustering Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes a novel approach that integrates Named Entity Recognition (NER) and LLM embeddings within a graph-based framework for document clustering. |
Imed Keraghel; Mohamed Nadif; | arxiv-cs.CL | 2024-12-19 |
| 719 | How Good Is GPT at Writing Political Speeches for The White House? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Using large language models (LLMs), computers are able to generate a written text in response to a us er request. |
Jacques Savoy; | arxiv-cs.CL | 2024-12-19 |
| 720 | A Full Transformer-based Framework for Automatic Pain Estimation Using Videos Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we present a novel full transformer-based framework consisting of a Transformer in Transformer (TNT) model and a Transformer leveraging cross-attention and self-attention blocks. |
Stefanos Gkikas; Manolis Tsiknakis; | arxiv-cs.CV | 2024-12-19 |
| 721 | LLMs As Mediators: Can They Diagnose Conflicts Accurately? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Prior research indicates that to be able to mediate conflict, observers of disagreements between parties must be able to reliably distinguish the sources of their disagreement as stemming from differences in beliefs about what is true (causality) vs. differences in what they value (morality). In this paper, we test if OpenAI’s Large Language Models GPT 3.5 and GPT 4 can perform this task and whether one or other type of disagreement proves particularly challenging for LLM’s to diagnose. |
Özgecan Koçak; Phanish Puranam; Afşar Yegin; | arxiv-cs.CL | 2024-12-19 |
| 722 | FarExStance: Explainable Stance Detection for Farsi Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce FarExStance, a new dataset for explainable stance detection in Farsi. |
MAJID ZARHARAN et. al. | arxiv-cs.CL | 2024-12-18 |
| 723 | Fake News Detection: Comparative Evaluation of BERT-like Models and Large Language Models with Generative AI-Annotated Data Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This study presents a comparative evaluation of BERT-like encoder-only models and autoregressive decoder-only large language models (LLMs) for fake news detection. |
Shaina Raza; Drai Paulen-Patterson; Chen Ding; | arxiv-cs.CL | 2024-12-18 |
| 724 | Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference IF:3 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. | arxiv-cs.CL | 2024-12-18 |
| 725 | Exploring Transformer-Augmented LSTM for Temporal and Spatial Feature Learning in Trajectory Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Here, a hybrid model that combines LSTMs for temporal encoding with a Transformer encoder for capturing complex interactions between vehicles is proposed. |
Chandra Raskoti; Weizi Li; | arxiv-cs.RO | 2024-12-17 |
| 726 | Lightweight Safety Classification Using Pruned Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce a novel technique for content safety and prompt injection classification for Large Language Models. |
Mason Sawtell; Tula Masterman; Sandi Besen; Jim Brown; | arxiv-cs.CL | 2024-12-17 |
| 727 | Investigating Mixture of Experts in Dense Retrieval Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: While Dense Retrieval Models (DRMs) have advanced Information Retrieval (IR), one limitation of these neural models is their narrow generalizability and robustness. To cope with … |
Effrosyni Sokli; Pranav Kasela; Georgios Peikos; Gabriella Pasi; | arxiv-cs.IR | 2024-12-16 |
| 728 | Causal Diffusion Transformers for Generative Modeling Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce Causal Diffusion as the autoregressive (AR) counterpart of Diffusion models. |
Chaorui Deng; Deyao Zhu; Kunchang Li; Shi Guang; Haoqi Fan; | arxiv-cs.CV | 2024-12-16 |
| 729 | No More Adam: Learning Rate Scaling at Initialization Is All You Need Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we question the necessity of adaptive gradient methods for training deep neural networks. |
Minghao Xu; Lichuan Xiang; Xu Cai; Hongkai Wen; | arxiv-cs.LG | 2024-12-16 |
| 730 | Seeing The Forest and The Trees: Solving Visual Graph and Tree Based Data Structure Problems Using Large Multimodal Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This research not only introduces an LMM benchmark to facilitate replication and further exploration but also underscores the potential of LMMs in solving complex computing problems, with important implications for pedagogy and assessment practices. |
SEBASTIAN GUTIERREZ et. al. | arxiv-cs.AI | 2024-12-15 |
| 731 | Optimized Quran Passage Retrieval Using An Expanded QA Dataset and Fine-Tuned Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The Qur’an QA 2023 shared task dataset had a limited number of questions with weak model retrieval. To address this challenge, this work updated the original dataset and improved the model accuracy. |
Mohamed Basem; Islam Oshallah; Baraa Hikal; Ali Hamdi; Ammar Mohamed; | arxiv-cs.CL | 2024-12-15 |
| 732 | Do Tutors Learn from Equity Training and Can Generative AI Assess It? Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We apply a mixed-method approach to analyze the performance of 81 undergraduate remote tutors. |
DANIELLE R. THOMAS et. al. | arxiv-cs.HC | 2024-12-15 |
| 733 | SusGen-GPT: A Data-Centric LLM for Financial NLP and Sustainability Report Generation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, open-source LLMs proficient in both finance and ESG domains remain scarce. To address this gap, we introduce SusGen-30K, a category-balanced dataset comprising seven financial NLP tasks and ESG report generation, and propose TCFD-Bench, a benchmark for evaluating sustainability report generation. |
QILONG WU et. al. | arxiv-cs.CL | 2024-12-14 |
| 734 | Tokens, The Oft-overlooked Appetizer: Large Language Models, The Distributional Hypothesis, and Meaning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Besides creating sub-optimal semantic building blocks and obscuring the model’s access to the necessary distributional patterns, we describe how tokenization pretraining can be a backdoor for bias and other unwanted content, which current alignment practices may not remediate. |
JULIA WITTE ZIMMERMAN et. al. | arxiv-cs.CL | 2024-12-14 |
| 735 | Does Multiple Choice Have A Future in The Age of Generative AI? A Posttest-only RCT Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Using a posttest-only randomized control design, we compare the performance of 234 tutors (790 lesson completions) across three conditions: MCQ only, open response only, and a combination of both. |
DANIELLE R. THOMAS et. al. | arxiv-cs.HC | 2024-12-13 |
| 736 | Evaluation of GPT-4o and GPT-4o-mini’s Vision Capabilities for Compositional Analysis from Dried Solution Drops Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Using OpenAI’s image-enabled language models, we analyzed deposits from 12 salts with 200 images per salt and per model. |
Deven B. Dangi; Beni B. Dangi; Oliver Steinbock; | arxiv-cs.CV | 2024-12-13 |
| 737 | 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. |
Senlin Cheng; Haopeng Sun; | arxiv-cs.CV | 2024-12-13 |
| 738 | NLPineers@ NLU of Devanagari Script Languages 2025: Hate Speech Detection Using Ensembling of BERT-based Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This work emphasizes the need for hate speech detection in Devanagari-scripted languages and presents a foundation for further research. |
Anmol Guragain; Nadika Poudel; Rajesh Piryani; Bishesh Khanal; | arxiv-cs.CL | 2024-12-11 |
| 739 | Advancing Single and Multi-task Text Classification Through Large Language Model Fine-tuning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study employed a diverse range of models and methods, varying in size and architecture, and including both fine-tuned and pre-trained approaches. |
Hang Zhao; Qile P. Chen; Yijing Barry Zhang; Gang Yang; | arxiv-cs.CL | 2024-12-11 |
| 740 | A Survey on Private Transformer Inference Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, their use in Machine Learning as a Service (MLaaS) raises significant privacy concerns, as centralized servers process sensitive user data. Private Transformer Inference (PTI) addresses these issues using cryptographic techniques such as Secure Multi-Party Computation (MPC) and Homomorphic Encryption (HE), enabling secure model inference without exposing inputs or models. |
Yang Li; Xinyu Zhou; Yitong Wang; Liangxin Qian; Jun Zhao; | arxiv-cs.CR | 2024-12-11 |
| 741 | Assessing Personalized AI Mentoring with Large Language Models in The Computing Field Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper provides an in-depth evaluation of three state-of-the-art Large Language Models (LLMs) for personalized career mentoring in the computing field, using three distinct student profiles that consider gender, race, and professional levels. |
Xiao Luo; Sean O’Connell; Shamima Mithun; | arxiv-cs.CL | 2024-12-11 |
| 742 | Generating Knowledge Graphs from Large Language Models: A Comparative Study of GPT-4, LLaMA 2, and BERT Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces a novel approach leveraging large language models (LLMs) like GPT-4, LLaMA 2 (13B), and BERT to generate KGs directly from unstructured data, bypassing traditional pipelines. |
Ahan Bhatt; Nandan Vaghela; Kush Dudhia; | arxiv-cs.CL | 2024-12-10 |
| 743 | 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 predictthe next token, implicitly learning a world model from which sequences aregenerated one token at a time? |
Raanan Y. Rohekar; Yaniv Gurwicz; Sungduk Yu; Estelle Aflalo; Vasudev Lal; | arxiv-cs.AI | 2024-12-10 |
| 744 | TrojanWhisper: Evaluating Pre-trained LLMs to Detect and Localize Hardware Trojans Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: For the first time, this paper explores the potential of general-purpose LLMs in detecting various HTs inserted in Register Transfer Level (RTL) designs, including SRAM, AES, and UART modules. We propose a novel tool for this goal that systematically assesses state-of-the-art LLMs (GPT-4o, Gemini 1.5 pro, and Llama 3.1) in detecting HTs without prior fine-tuning. |
Md Omar Faruque; Peter Jamieson; Ahmad Patooghy; Abdel-Hameed A. Badawy; | arxiv-cs.CR | 2024-12-10 |
| 745 | Rethinking Emotion Annotations in The Era of Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we analyze the complexities of emotion annotation in the context of LLMs, focusing on GPT-4 as a leading model. |
Minxue Niu; Yara El-Tawil; Amrit Romana; Emily Mower Provost; | arxiv-cs.CL | 2024-12-10 |
| 746 | GPT-2 Through The Lens of Vector Symbolic Architectures Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper explores the resemblance between decoder-only transformer architecture and vector symbolic architectures (VSA) and presents experiments indicating that GPT-2 uses mechanisms involving nearly orthogonal vector bundling and binding operations similar to VSA for computation and communication between layers. |
Johannes Knittel; Tushaar Gangavarapu; Hendrik Strobelt; Hanspeter Pfister; | arxiv-cs.LG | 2024-12-10 |
| 747 | Automatic Item Generation for Personality Situational Judgment Tests with Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Two studies were conducted: Study 1 evaluated the impact of prompt design and temperature settings on content validity, finding that optimized prompts with a temperature of 1.0 produced creative and accurate items. Study 2 assessed the psychometric properties of GPT-4-generated PSJTs, revealing that they demonstrated satisfactory reliability and validity, surpassing the performance of manually developed tests in measuring the Big Five personality traits. |
Chang-Jin Li; Jiyuan Zhang; Yun Tang; Jian Li; | arxiv-cs.CL | 2024-12-10 |
| 748 | Towards Predictive Communication with Brain-Computer Interfaces Integrating Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This perspective article aims at providing an outline of the state of the art and future developments towards the integration of cutting-edge predictive language models with BCI. |
Andrea Caria; | arxiv-cs.HC | 2024-12-10 |
| 749 | Inverting Visual Representations with Detection Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we apply the approach of training inverse models to reconstruct input images from intermediate layers within a Detection Transformer, showing that this approach is efficient and feasible for transformer-based vision models. |
Jan Rathjens; Shirin Reyhanian; David Kappel; Laurenz Wiskott; | arxiv-cs.CV | 2024-12-09 |
| 750 | 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 Coarse-to-Fine AutoRegressive Policy (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. | arxiv-cs.RO | 2024-12-09 |
| 751 | Optimizing Multi-Task Learning for Enhanced Performance in Large Language Models Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This study aims to explore the performance improvement method of large language models based on GPT-4 under the multi-task learning framework and conducts experiments on two … |
ZHEN QI et. al. | ArXiv | 2024-12-09 |
| 752 | 100% Elimination of Hallucinations on RAGTruth for GPT-4 and GPT-3.5 Turbo Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we introduce Acurai, a novel systematic approach that achieves 100% hallucination-free responses in LLMs by reformatting queries and context data prior to input. |
Michael C. Wood; Adam A. Forbes; | arxiv-cs.CL | 2024-12-06 |
| 753 | SplaXBERT: Leveraging Mixed Precision Training and Context Splitting for Question Answering Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: SplaXBERT, built on ALBERT-xlarge with context-splitting and mixed precision training, achieves high efficiency in question-answering tasks on lengthy texts. Tested on SQuAD v1.1, … |
Zhu Yufan; Hao Zeyu; Li Siqi; Niu Boqian; | arxiv-cs.CL | 2024-12-06 |
| 754 | Exploring Transformer-Based Music Overpainting for Jazz Piano Variations Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce VAR4000, a subset of a larger dataset for jazz piano performances, consisting of 4,352 training pairs. |
Eleanor Row; Ivan Shanin; György Fazekas; | arxiv-cs.SD | 2024-12-05 |
| 755 | ChatNVD: Advancing Cybersecurity Vulnerability Assessment with Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce ChatNVD, a support tool powered by Large Language Models (LLMs) that leverages the National Vulnerability Database (NVD) to generate accessible, context-rich summaries of software vulnerabilities. |
Shivansh Chopra; Hussain Ahmad; Diksha Goel; Claudia Szabo; | arxiv-cs.CR | 2024-12-05 |
| 756 | FANAL — Financial Activity News Alerting Language Modeling Framework Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces FANAL (Financial Activity News Alerting Language Modeling Framework), a specialized BERT-based framework engineered for real-time financial event detection and analysis, categorizing news into twelve distinct financial categories. |
Urjitkumar Patel; Fang-Chun Yeh; Chinmay Gondhalekar; Hari Nalluri; | arxiv-cs.CL | 2024-12-04 |
| 757 | Controlling The Mutation in Large Language Models for The Efficient Evolution of Algorithms Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces a novel approach to mutation control within LLM-driven evolutionary frameworks, inspired by theory of genetic algorithms. |
Haoran Yin; Anna V. Kononova; Thomas Bäck; Niki van Stein; | arxiv-cs.NE | 2024-12-04 |
| 758 | A Water Efficiency Dataset for African Data Centers Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: AI computing and data centers consume a large amount of freshwater, both directly for cooling and indirectly for electricity generation. While most attention has been paid to … |
Noah Shumba; Opelo Tshekiso; Pengfei Li; Giulia Fanti; Shaolei Ren; | arxiv-cs.LG | 2024-12-04 |
| 759 | Transformer-Based Auxiliary Loss for Face Recognition Across Age Variations Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a technique for loss evaluation that uses a transformer network as an additive loss in the face recognition domain. |
Pritesh Prakash; Ashish Jacob Sam; S Umamaheswaran; | arxiv-cs.CV | 2024-12-03 |
| 760 | The Asymptotic Behavior 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; | arxiv-cs.AI | 2024-12-03 |
| 761 | Achieving Semantic Consistency: Contextualized Word Representations for Political Text Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study compares Word2Vec and BERT using 20 years of People’s Daily articles to evaluate their performance in semantic representations across different timeframes. |
Ruiyu Zhang; Lin Nie; Ce Zhao; Qingyang Chen; | arxiv-cs.CL | 2024-12-03 |
| 762 | Impact of Data Snooping on Deep Learning Models for Locating Vulnerabilities in Lifted Code Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study examines the impact of data snooping on neural networks used to detect vulnerabilities in lifted code, and builds on previous research that used word2vec and unidirectional and bidirectional transformer-based embeddings. |
Gary A. McCully; John D. Hastings; Shengjie Xu; | arxiv-cs.CR | 2024-12-02 |
| 763 | Su-RoBERTa: A Semi-supervised Approach to Predicting Suicide Risk Through Social Media Using Base Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose Su-RoBERTa, a fine-tuned RoBERTa on suicide risk prediction task that utilized both the labeled and unlabeled Reddit data and tackled class imbalance by data augmentation using GPT-2 model. |
CHAYAN TANK et. al. | arxiv-cs.HC | 2024-12-02 |
| 764 | Efficiency of LLMs in Identifying Abusive Language Online: A Comparative Study of LSTM, BERT, and GPT Related Papers Related Patents Related Grants Related Venues Related Experts View |
Zaur Gouliev; Rajesh R. Jaiswal; | HCAIep | 2024-12-02 |
| 765 | Assessing GPT Model Uncertainty in Mathematical OCR Tasks Via Entropy Analysis Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper investigates the uncertainty of Generative Pre-trained Transformer (GPT) models in extracting mathematical equations from images of varying resolutions and converting them into LaTeX code. |
Alexei Kaltchenko; | arxiv-cs.IT | 2024-12-02 |
| 766 | Sequence Length Independent Norm-Based Generalization Bounds for Transformers Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper provides norm-based generalization bounds for the Transformer architecture that do not depend on the input sequence length. |
Jacob Trauger; Ambuj Tewari; | aistats | 2024-12-01 |
| 767 | TGTOD: A Global Temporal Graph Transformer for Outlier Detection at Scale Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we rethink temporal graph Transformers and propose TGTOD, a novel end-to-end Temporal Graph Transformer for Outlier Detection. |
Kay Liu; Jiahao Ding; MohamadAli Torkamani; Philip S. Yu; | arxiv-cs.LG | 2024-12-01 |
| 768 | Analysis of Privacy Leakage in Federated Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: With the rapid adoption of Federated Learning (FL) as the training and tuning protocol for applications utilizing Large Language Models (LLMs), recent research highlights the need for significant modifications to FL to accommodate the large-scale of LLMs. |
Minh Vu; Truc Nguyen; Tre� Jeter; My T. Thai; | aistats | 2024-12-01 |
| 769 | Enhancing In-context Learning Via Linear Probe Calibration Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This approach uses prompts that include in-context demonstrations to generate the corresponding output for a new query input. |
MOMIN ABBAS et. al. | aistats | 2024-12-01 |
| 770 | Automated Extraction of Acronym-Expansion Pairs from Scientific Papers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This project addresses challenges posed by the widespread use of abbreviations and acronyms in digital texts. We propose a novel method that combines document preprocessing, regular expressions, and a large language model to identify abbreviations and map them to their corresponding expansions. |
Izhar Ali; Million Haileyesus; Serhiy Hnatyshyn; Jan-Lucas Ott; Vasil Hnatyshin; | arxiv-cs.CL | 2024-12-01 |
| 771 | Understanding Complex-Valued Transformer for Modulation Recognition Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Complex-valued convolution neural networks (CVCNNs) have been recently applied for modulation recognition (MR), due to its ability to capture the relationship between the real and … |
JINGRENG LEI et. al. | IEEE Wireless Communications Letters | 2024-12-01 |
| 772 | A Direct Modularization Method for Multi-cell to Multi-cell Equalizer With Large Cell Count Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: A modular voltage equalizer can be used in a wide variety of applications without changing the module design. However, the modularization of an equalizer topology often involves … |
S. K. Dam; Vinod John; | IEEE Transactions on Industrial Electronics | 2024-12-01 |
| 773 | How Does GPT-2 Predict Acronyms? Extracting and Understanding A Circuit Via Mechanistic Interpretability Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we focus on understanding how GPT-2 Small performs the task of predicting three-letter acronyms. |
Jorge Garc�a-Carrasco; Alejandro Mat�; Juan Carlos Trujillo; | aistats | 2024-12-01 |
| 774 | Forma Mentis Networks Predict Creativity Ratings of Short Texts Via Interpretable Artificial Intelligence in Human and GPT-simulated Raters Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We use textual forma mentis networks (TFMN) to extract network (semantic/syntactic associations) and emotional features from approximately one thousand human- and GPT3.5-generated stories. |
Edith Haim; Natalie Fischer; Salvatore Citraro; Giulio Rossetti; Massimo Stella; | arxiv-cs.AI | 2024-11-30 |
| 775 | Homeostasis and Sparsity in Transformer Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The transformer architecture has become an integral part of the field of modern neural networks, playing a crucial role in a variety of tasks, such as text generation, machine … |
Leonid Kotyuzanskiy; Artem Klimov; | arxiv-cs.LG | 2024-11-30 |
| 776 | LLM Teacher-Student Framework for Text Classification With No Manually Annotated Data: A Case Study in IPTC News Topic Classification Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: With the ever-increasing number of news stories available online, classifying them by topic, regardless of the language they are written in, has become crucial for enhancing readers’ access to relevant content. To address this challenge, we propose a teacher-student framework based on large language models (LLMs) for developing multilingual news classification models of reasonable size with no need for manual data annotation. |
Taja Kuzman; Nikola Ljubešić; | arxiv-cs.CL | 2024-11-29 |
| 777 | Habit Coach: Customising RAG-based Chatbots to Support Behavior Change Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents the iterative development of Habit Coach, a GPT-based chatbot designed to support users in habit change through personalized interaction. |
Arian Fooroogh Mand Arabi; Cansu Koyuturk; Michael O’Mahony; Raffaella Calati; Dimitri Ognibene; | arxiv-cs.HC | 2024-11-28 |
| 778 | Waterfall Transformer for Multi-person Pose Estimation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose the Waterfall Transformer architecture for Pose estimation (WTPose), a single-pass, end-to-end trainable framework designed for multi-person pose estimation. |
Navin Ranjan; Bruno Artacho; Andreas Savakis; | arxiv-cs.CV | 2024-11-28 |
| 779 | The Impact of Example Selection in Few-Shot Prompting on Automated Essay Scoring Using GPT Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study investigates the impact of example selection on the performance of au-tomated essay scoring (AES) using few-shot prompting with GPT models. |
Lui Yoshida; | arxiv-cs.CL | 2024-11-28 |
| 780 | SmartLLMSentry: A Comprehensive LLM Based Smart Contract Vulnerability Detection Framework Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces SmartLLMSentry, a novel framework that leverages large language models (LLMs), specifically ChatGPT with in-context training, to advance smart contract vulnerability detection. |
Oualid Zaazaa; Hanan El Bakkali; | arxiv-cs.CR | 2024-11-28 |
| 781 | Automated Literature Review Using NLP Techniques and LLM-Based Retrieval-Augmented Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Developing a system capable of automatically generating the literature reviews from only the PDF files as input is the primary objective of this research work. |
Nurshat Fateh Ali; Md. Mahdi Mohtasim; Shakil Mosharrof; T. Gopi Krishna; | arxiv-cs.CL | 2024-11-27 |
| 782 | Training and Evaluating Language Models with Template-based Data Generation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, these models often struggle with tasks requiring complex reasoning, particularly in mathematical problem-solving, due in part to the scarcity of large-scale, high-quality, domain-specific datasets necessary for training sophisticated reasoning abilities. To address this limitation, we introduce Template-based Data Generation (TDG), a novel approach that leverages LLMs (GPT-4) to automatically generate parameterized meta-templates, which are then used to synthesize a vast array of high-quality problems and solutions. |
Yifan Zhang; | arxiv-cs.CL | 2024-11-27 |
| 783 | CLOVER: Cross-Layer Orthogonal Vectors Pruning and Fine-Tuning Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Decoder-only models generate tokens autoregressively by caching key/value vectors, but as the cache grows, inference becomes memory-bound. To address this issue, we introduce CLOVER (Cross-Layer Orthogonal Vectors), a novel approach that treats pairs of attention layers as a set of low-rank decompositions. |
Fanxu Meng; Pingzhi Tang; Fan jiang; Muhan Zhang; | arxiv-cs.LG | 2024-11-26 |
| 784 | On Limitations of LLM As Annotator for Low Resource Languages Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To bridge this gap, Large Language Models (LLMs) present an opportunity for potential annotators, capable of generating datasets and resources for these underrepresented languages. In this paper, we focus on Marathi, a low-resource language, and evaluate the performance of both closed-source and open-source LLMs as annotators, while also comparing these results with fine-tuned BERT models. |
Suramya Jadhav; Abhay Shanbhag; Amogh Thakurdesai; Ridhima Sinare; Raviraj Joshi; | arxiv-cs.CL | 2024-11-26 |
| 785 | Give Me The Code — Log Analysis of First-Year CS Students’ Interactions With GPT Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Despite using unsophisticated prompting techniques, our findings suggest that the majority of students successfully leveraged GPT, incorporating the suggested solutions into their projects. |
Pedro Alves; Bruno Pereira Cipriano; | arxiv-cs.CY | 2024-11-26 |
| 786 | Distributed Sign Momentum with Local Steps for Training Transformers Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: For generic base optimizers, by approximating the sign operator with a randomized version that acts as a continuous analog in expectation, we present a general convergence analysis, which specializes to an $O(1/\sqrt{T})$ rate for a particular instance. |
SHUHUA YU et. al. | arxiv-cs.LG | 2024-11-26 |
| 787 | What Differentiates Educational Literature? A Multimodal Fusion Approach of Transformers and Computational Linguistics Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The integration of new literature into the English curriculum remains a challenge since educators often lack scalable tools to rapidly evaluate readability and adapt texts for diverse classroom needs. This study proposes to address this gap through a multimodal approach that combines transformer-based text classification with linguistic feature analysis to align texts with UK Key Stages. |
Jordan J. Bird; | arxiv-cs.CL | 2024-11-26 |
| 788 | Give Me The Code – Log Analysis of First-Year CS Students’ Interactions With GPT Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The impact of Large Language Models (LLMs) like GPT-3, GPT-4, and Bard in computer science (CS) education is expected to be profound. Students now have the power to generate code … |
P. Alves; Bruno Pereira Cipriano; | ArXiv | 2024-11-26 |
| 789 | Can Artificial Intelligence Predict Clinical Trial Outcomes? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study evaluates the performance of large language models (LLMs) and the HINT model in predicting clinical trial outcomes, focusing on metrics including Balanced Accuracy, Matthews Correlation Coefficient (MCC), Recall, and Specificity. |
Shuyi Jin; Lu Chen; Hongru Ding; Meijie Wang; Lun Yu; | arxiv-cs.LG | 2024-11-26 |
| 790 | Can Bidirectional Encoder Become The Ultimate Winner for Downstream Applications of Foundation Models? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This article analyzes one-way and bidirectional models based on GPT and BERT and compares their differences based on the purpose of the model. |
Lewen Yang; Xuanyu Zhou; Juao Fan; Xinyi Xie; Shengxin Zhu; | arxiv-cs.CL | 2024-11-26 |
| 791 | An Attempt to Develop A Neural Parser Based on Simplified Head-Driven Phrase Structure Grammar on Vietnamese Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we aimed to develop a neural parser for Vietnamese based on simplified Head-Driven Phrase Structure Grammar (HPSG). |
Duc-Vu Nguyen; Thang Chau Phan; Quoc-Nam Nguyen; Kiet Van Nguyen; Ngan Luu-Thuy Nguyen; | arxiv-cs.CL | 2024-11-26 |
| 792 | The Importance of Visual Modelling Languages in Generative Software Engineering Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: GPT-4 accepts image and text inputs, rather than simply natural language. We investigate relevant use cases stemming from these enhanced capabilities of GPT-4. |
Roberto Rossi; | arxiv-cs.SE | 2024-11-26 |
| 793 | Can AI Grade Your Essays? A Comparative Analysis of Large Language Models and Teacher Ratings in Multidimensional Essay Scoring Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Recent developments in generative AI, such as large language models, offer potential solutions to facilitate essay-scoring tasks for teachers. |
Kathrin Seßler; Maurice Fürstenberg; Babette Bühler; Enkelejda Kasneci; | arxiv-cs.CL | 2024-11-25 |
| 794 | Development of Pre-Trained Transformer-based Models for The Nepali Language Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: While existing efforts have predominantly concentrated on basic encoder-based models, there is a notable gap in the exploration of decoder-based architectures. To address this gap, we have collected 27.5 GB of Nepali text data, approximately 2.4x larger than any previously available Nepali language corpus. |
Prajwal Thapa; Jinu Nyachhyon; Mridul Sharma; Bal Krishna Bal; | arxiv-cs.CL | 2024-11-24 |
| 795 | Nimbus: Secure and Efficient Two-Party Inference for Transformers Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This work presents a new two-party inference framework $\mathsf{Nimbus}$ for Transformer models. |
ZHENGYI LI et. al. | arxiv-cs.CR | 2024-11-23 |
| 796 | All That Glitters: Approaches to Evaluations with Unreliable Model and Human Annotations Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The effects of this error can escape commonly reported metrics of label quality or obscure questions of accuracy, bias, fairness, and usefulness during model evaluation. This study demonstrates methods for answering such questions even in the context of very low reliabilities from expert humans. |
Michael Hardy; | arxiv-cs.CL | 2024-11-23 |
| 797 | 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: To tackle these problems, we first propose a task decomposition evaluation framework based on GPT-4o to automatically construct a new training dataset, where the complex evaluation task is decoupled into simpler sub-tasks, effectively reducing the learning complexity. Based on this dataset, we design innovative training strategies to effectively distill GPT-4o’s evaluation capabilities into a 7B open-source MLLM, MiniCPM-V-2.6. |
RONG-CHENG TU et. al. | arxiv-cs.CL | 2024-11-23 |
| 798 | Enhancing Grammatical Error Detection Using BERT with Cleaned Lang-8 Dataset Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper presents an improved LLM based model for Grammatical Error Detection (GED), which is a very challenging and equally important problem for many applications. |
Rahul Nihalani; Kushal Shah; | arxiv-cs.CL | 2024-11-23 |
| 799 | Improving Next Tokens Via Second-to-Last Predictions with Generate and Refine Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We use our model to improve the next token predictions of a standard GPT by combining both predictions in a “generate-then-refine” approach. |
Johannes Schneider; | arxiv-cs.CL | 2024-11-23 |
| 800 | Astro-HEP-BERT: A Bidirectional Language Model for Studying The Meanings of Concepts in Astrophysics and High Energy Physics Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: I present Astro-HEP-BERT, a transformer-based language model specifically designed for generating contextualized word embeddings (CWEs) to study the meanings of concepts in astrophysics and high-energy physics. |
Arno Simons; | arxiv-cs.CL | 2024-11-22 |
| 801 | Inducing Human-like Biases in Moral Reasoning Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we study the alignment (BrainScore) of large language models (LLMs) fine-tuned for moral reasoning on behavioral data and/or brain data of humans performing the same task. |
ARTEM KARPOV et. al. | arxiv-cs.AI | 2024-11-22 |
| 802 | Purrfessor: A Fine-tuned Multimodal LLaVA Diet Health Chatbot Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study introduces Purrfessor, an innovative AI chatbot designed to provide personalized dietary guidance through interactive, multimodal engagement. |
Linqi Lu; Yifan Deng; Chuan Tian; Sijia Yang; Dhavan Shah; | arxiv-cs.HC | 2024-11-22 |
| 803 | A Comparative Analysis of Transformer and LSTM Models for Detecting Suicidal Ideation on Reddit Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Our findings show that transformer-based models have the potential to improve suicide ideation detection, thereby providing a path to develop robust mental health monitoring tools from social media. This research, therefore, underlines the undeniable prospect of advanced techniques in Natural Language Processing (NLP) while improving suicide prevention efforts. |
Khalid Hasan; Jamil Saquer; | arxiv-cs.LG | 2024-11-22 |
| 804 | Who Can Withstand Chat-Audio Attacks? An Evaluation Benchmark for Large Audio-Language Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: While existing research focused on model-specific adversarial methods, real-world applications demand a more generalizable and universal approach to audio adversarial attacks. In this paper, we introduce the Chat-Audio Attacks (CAA) benchmark including four distinct types of audio attacks, which aims to explore the vulnerabilities of LALMs to these audio attacks in conversational scenarios. |
Wanqi Yang; Yanda Li; Meng Fang; Yunchao Wei; Ling Chen; | arxiv-cs.SD | 2024-11-22 |
| 805 | Foundation Models for Wearable Movement Data in Mental Health Research Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce thePretrained Actigraphy Transformer (PAT), the first open source foundation modeldesigned for time-series wearable movement data. |
Franklin Y. Ruan; Aiwei Zhang; Jenny Y. Oh; SouYoung Jin; Nicholas C. Jacobson; | arxiv-cs.LG | 2024-11-21 |
| 806 | Multiset Transformer: Advancing Representation Learning in Persistence Diagrams Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To improve persistence diagram representation learning, we propose Multiset Transformer. |
Minghua Wang; Ziyun Huang; Jinhui Xu; | arxiv-cs.LG | 2024-11-21 |
| 807 | GPT Versus Humans: Uncovering Ethical Concerns in Conversational Generative AI-empowered Multi-Robot Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The objectives of the study were to examine novel ethical issues arising from the application of LLMs in multi-robot systems. |
REBEKAH ROUSI et. al. | arxiv-cs.RO | 2024-11-21 |
| 808 | Comparative Analysis of Pooling Mechanisms in LLMs: A Sentiment Analysis Perspective Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Despite their widespread use, the comparative performance of these strategies on different LLM architectures remains underexplored. To address this gap, this paper investigates the effects of these pooling mechanisms on two prominent LLM families — BERT and GPT, in the context of sentence-level sentiment analysis. |
Jinming Xing; Dongwen Luo; Chang Xue; Ruilin Xing; | arxiv-cs.CL | 2024-11-21 |
| 809 | Evaluating The Robustness of Analogical Reasoning in Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: On digit-matrix problems, we find a similar pattern but only on one out of the two types of variants we tested. |
Martha Lewis; Melanie Mitchell; | arxiv-cs.CL | 2024-11-21 |
| 810 | BERT-Based Approach for Automating Course Articulation Matrix Construction with Explainable AI Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this study, We experiment with four models from the BERT family: BERT Base, DistilBERT, ALBERT, and RoBERTa, and use multiclass classification to assess the alignment between CO and PO/PSO pairs. |
Natenaile Asmamaw Shiferaw; Simpenzwe Honore Leandre; Aman Sinha; Dillip Rout; | arxiv-cs.LG | 2024-11-21 |
| 811 | Explaining GPT-4’s Schema of Depression Using Machine Behavior Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we leveraged contemporary measurement theory to decode how GPT-4 interrelates depressive symptoms to inform both clinical utility and theoretical understanding. |
ADITHYA V GANESAN et. al. | arxiv-cs.CL | 2024-11-20 |
| 812 | Exploring Large Language Models for Climate Forecasting Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we investigate the capability of GPT-4 in predicting rainfall at short-term (15-day) and long-term (12-month) scales. |
Yang Wang; Hassan A. Karimi; | arxiv-cs.LG | 2024-11-20 |
| 813 | Topkima-Former: Low-energy, Low-Latency Inference for Transformers Using Top-k In-memory ADC Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Hence, we propose innovations at the circuit, architecture, and algorithm levels to accelerate the transformer. |
SHUAI DONG et. al. | arxiv-cs.AR | 2024-11-20 |
| 814 | AI-Driven Agents with Prompts Designed for High Agreeableness Increase The Likelihood of Being Mistaken for A Human in The Turing Test Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Various explanations in the literature address why these GPT agents were perceived as human, including psychological frameworks for understanding anthropomorphism. These findings highlight the importance of personality engineering as an emerging discipline in artificial intelligence, calling for collaboration with psychology to develop ergonomic psychological models that enhance system adaptability in collaborative activities. |
U. LEÓN-DOMÍNGUEZ et. al. | arxiv-cs.AI | 2024-11-20 |
| 815 | SynEHRgy: Synthesizing Mixed-Type Structured Electronic Health Records Using Decoder-Only Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a novel tokenization strategy tailored for structured EHR data, which encompasses diverse data types such as covariates, ICD codes, and irregularly sampled time series. |
Hojjat Karami; David Atienza; Anisoara Ionescu; | arxiv-cs.LG | 2024-11-20 |
| 816 | Video-RAG: Visually-aligned Retrieval-Augmented Long Video Comprehension Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose Video Retrieval-Augmented Generation (Video-RAG), a training-free and cost-effective pipeline that employs visually-aligned auxiliary texts to help facilitate cross-modality alignment while providing additional information beyond the visual content. |
YONGDONG LUO et. al. | arxiv-cs.CV | 2024-11-20 |
| 817 | Transformer-Based Contextualized Language Models Joint with Neural Networks for Natural Language Inference in Vietnamese Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This article aims to introduce a novel approach or model that attains improved performance for Vietnamese NLI. |
Dat Van-Thanh Nguyen; Tin Van Huynh; Kiet Van Nguyen; Ngan Luu-Thuy Nguyen; | arxiv-cs.CL | 2024-11-20 |
| 818 | Benchmarking GPT-4 Against Human Translators: A Comprehensive Evaluation Across Languages, Domains, and Expertise Levels Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This study presents a comprehensive evaluation of GPT-4’s translation capabilities compared to human translators of varying expertise levels. |
JIANHAO YAN et. al. | arxiv-cs.CL | 2024-11-20 |
| 819 | Evaluating Tokenizer Performance of Large Language Models Across Official Indian Languages Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a comprehensive evaluation of tokenizers used by 12 LLMs across all 22 official languages of India, with a focus on comparing the efficiency of their tokenization processes. |
S. Tamang; D. J. Bora; | arxiv-cs.CL | 2024-11-19 |
| 820 | Leveraging Virtual Reality and AI Tutoring for Language Learning: A Case Study of A Virtual Campus Environment with OpenAI GPT Integration with Unity 3D Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a new approach to multiple language learning, with Hindi the language to be learnt in our case, by using the integration of virtual reality environments and AI enabled tutoring systems using OpenAIs GPT api calls. |
Adithya TG; Abhinavaram N; Gowri Srinivasa; | arxiv-cs.HC | 2024-11-19 |
| 821 | The Illusion of Empathy: How AI Chatbots Shape Conversation Perception Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This study examines how chatbot identity and perceived empathy influence users’ overall conversation experience. |
TINGTING LIU et. al. | arxiv-cs.HC | 2024-11-19 |
| 822 | Enhancing Multi-Class Disease Classification: Neoplasms, Cardiovascular, Nervous System, and Digestive Disorders Using Advanced LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this research, we explored the improvement in terms of multi-class disease classification via pre-trained language models over Medical-Abstracts-TC-Corpus that spans five medical conditions. |
Ahmed Akib Jawad Karim; Muhammad Zawad Mahmud; Samiha Islam; Aznur Azam; | arxiv-cs.CL | 2024-11-19 |
| 823 | Strengthening False Information Propagation Detection: Leveraging SVM and Sophisticated Text Vectorization Techniques in Comparison to BERT Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study exploresthe utilization of machine learning and natural language processing,specifically Support Vector Machines (SVM) and BERT, to detect fake news. Weemploy three distinct text vectorization methods for SVM: Term FrequencyInverse Document Frequency (TF-IDF), Word2Vec, and Bag of Words (BoW),evaluating their effectiveness in distinguishing between genuine and fake news.Additionally, we compare these methods against the transformer large languagemodel, BERT. |
Ahmed Akib Jawad Karim; Kazi Hafiz Md Asad; Aznur Azam; | arxiv-cs.CL | 2024-11-19 |
| 824 | Chapter 7 Review of Data-Driven Generative AI Models for Knowledge Extraction from Scientific Literature in Healthcare Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This review examines the development of abstractive NLP-based text summarization approaches and compares them to existing techniques for extractive summarization. |
Leon Kopitar; Primoz Kocbek; Lucija Gosak; Gregor Stiglic; | arxiv-cs.CL | 2024-11-18 |
| 825 | A Combined Encoder and Transformer Approach for Coherent and High-Quality Text Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This research introduces a novel text generation model that combines BERT’s semantic interpretation strengths with GPT-4’s generative capabilities, establishing a high standard in generating coherent, contextually accurate language. |
JIAJING CHEN et. al. | arxiv-cs.CL | 2024-11-18 |
| 826 | PerfCodeGen: Improving Performance of LLM Generated Code with Execution Feedback Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: Large Language Models (LLMs) are widely adopted for assisting in software development tasks, yet their performance evaluations have narrowly focused on the functional correctness … |
YUN PENG et. al. | ArXiv | 2024-11-18 |
| 827 | Automatic A-C. Network Switching Units Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The desirable characteristics of automatic switching units designed for application in secondary a-c. distribution networks are discussed in this paper. Descriptions are given of … |
G. G. Grissinger; | Journal of the A.I.E.E. | |
| 828 | CNMBERT: A Model for Converting Hanyu Pinyin Abbreviations to Chinese Characters Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This task typically involves text-length alignment and seems easy to solve; however, due to the limited information content in pinyin abbreviations, achieving accurate conversion is challenging. In this paper, we treat this as a fill-mask task and propose CNMBERT, which stands for zh-CN Pinyin Multi-mask BERT Model, as a solution to this issue. |
Zishuo Feng; Feng Cao; | arxiv-cs.CL | 2024-11-18 |
| 829 | Re-examining Learning Linear Functions in Context Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We explore a simple model of ICL in a controlled setup with synthetic training data to investigate ICL of univariate linear functions. |
Omar Naim; Guilhem Fouilhé; Nicholas Asher; | arxiv-cs.LG | 2024-11-18 |
| 830 | Multi-Grained Preference Enhanced Transformer for Multi-Behavior Sequential Recommendation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: On the other hand, the dynamic multi-grained behavior-aware preference is hard to capture in interaction sequences, which reflects interaction-aware sequential pattern. To tackle these challenges, we propose a Multi-Grained Preference enhanced Transformer framework (M-GPT). |
CHUAN HE et. al. | arxiv-cs.IR | 2024-11-18 |
| 831 | Knowledge-enhanced Transformer for Multivariate Long Sequence Time-series Forecasting Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce a novel approach that encapsulates conceptual relationships among variables within a well-defined knowledge graph, forming dynamic and learnable KGEs for seamless integration into the transformer architecture. |
Shubham Tanaji Kakde; Rony Mitra; Jasashwi Mandal; Manoj Kumar Tiwari; | arxiv-cs.LG | 2024-11-17 |
| 832 | Brain-inspired Action Generation with Spiking Transformer Diffusion Policy Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Especially in Can task, we achieved an improvement of 8%. |
Qianhao Wang; Yinqian Sun; Enmeng Lu; Qian Zhang; Yi Zeng; | arxiv-cs.RO | 2024-11-15 |
| 833 | Does Prompt Formatting Have Any Impact on LLM Performance? IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Although previous research has explored aspects like rephrasing prompt contexts, using various prompting techniques (like in-context learning and chain-of-thought), and ordering few-shot examples, our understanding of LLM sensitivity to prompt templates remains limited. Therefore, this paper examines the impact of different prompt templates on LLM performance. |
JIA HE et. al. | arxiv-cs.CL | 2024-11-15 |
| 834 | CMATH: Cross-Modality Augmented Transformer with Hierarchical Variational Distillation for Multimodal Emotion Recognition in Conversation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel Cross-Modality Augmented Transformer with Hierarchical Variational Distillation, called CMATH, which consists of two major components, i.e., Multimodal Interaction Fusion and Hierarchical Variational Distillation. |
XIAOFEI ZHU et. al. | arxiv-cs.MM | 2024-11-15 |
| 835 | KuaiFormer: Transformer-Based Retrieval at Kuaishou Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce KuaiFormer, a novel transformer-based retrieval framework deployed in a large-scale content recommendation system. |
CHI LIU et. al. | arxiv-cs.IR | 2024-11-15 |
| 836 | Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Although many model compression approaches have been explored, they often suffer from notorious performance degradation. To address this issue, we introduce a new method, namely Transformer Re-parameterization, to boost the performance of lightweight Transformer models. |
Zixing Zhang; Zhongren Dong; Weixiang Xu; Jing Han; | arxiv-cs.SD | 2024-11-14 |
| 837 | Adopting RAG for LLM-Aided Future Vehicle Design Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we explore the integration of Large Language Models (LLMs) with Retrieval-Augmented Generation (RAG) to enhance automated design and software development in the automotive industry. |
Vahid Zolfaghari; Nenad Petrovic; Fengjunjie Pan; Krzysztof Lebioda; Alois Knoll; | arxiv-cs.SE | 2024-11-14 |
| 838 | BabyLM Challenge: Exploring The Effect of Variation Sets on Language Model Training Efficiency Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In the context of the BabyLM Challenge, we focus on Variation Sets (VSs), sets of consecutive utterances expressing a similar intent with slightly different words and structures, which are ubiquitous in CDS. |
Akari Haga; Akiyo Fukatsu; Miyu Oba; Arianna Bisazza; Yohei Oseki; | arxiv-cs.CL | 2024-11-14 |
| 839 | Is Small Really Beautiful for Central Bank Communication? Evaluating Language Models for Finance: Llama-3-70B, GPT-4, FinBERT-FOMC, FinBERT, and VADER Related Papers Related Patents Related Grants Related Venues Related Experts View |
Wonseong Kim; J. Spörer; Choong Lyol Lee; Siegfried Handschuh; | International Conference on AI in Finance | 2024-11-14 |
| 840 | LoRA-LiteE: A Computationally Efficient Framework for Chatbot Preference-Tuning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, RLHF methods are often computationally intensive and resource-demanding, limiting their scalability and accessibility for broader applications. To address these challenges, this study introduces LoRA-Lite Ensemble (LoRA-LiteE), an innovative framework that combines Supervised Fine-tuning (SFT) with Low-Rank Adaptation (LoRA) and Ensemble Learning techniques to effectively aggregate predictions of lightweight models, which aim to achieve a balance between the performance and computational cost. |
Yahe Yang; Chunliang Tao; Xiaojing Fan; | arxiv-cs.CL | 2024-11-14 |
| 841 | CamemBERT 2.0: A Smarter French Language Model Aged to Perfection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This issue emphasizes the need for updated models that reflect current linguistic trends. In this paper, we introduce two new versions of the CamemBERT base model-CamemBERTav2 and CamemBERTv2-designed to address these challenges. |
WISSAM ANTOUN et. al. | arxiv-cs.CL | 2024-11-13 |
| 842 | Evaluating World Models with LLM for Decision Making Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a comprehensive evaluation of the world models with LLMs from the decision making perspective. |
Chang Yang; Xinrun Wang; Junzhe Jiang; Qinggang Zhang; Xiao Huang; | arxiv-cs.AI | 2024-11-13 |
| 843 | LSH-MoE: Communication-efficient MoE Training Via Locality-Sensitive Hashing Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose LSH-MoE, a communication-efficient MoE training framework using locality-sensitive hashing (LSH). |
XIAONAN NIE et. al. | arxiv-cs.DC | 2024-11-13 |
| 844 | Towards Optimizing A Retrieval Augmented Generation Using Large Language Model on Academic Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Given the growing trend of many organizations integrating Retrieval Augmented Generation (RAG) into their operations, we assess RAG on domain-specific data and test state-of-the-art models across various optimization techniques. |
Anum Afzal; Juraj Vladika; Gentrit Fazlija; Andrei Staradubets; Florian Matthes; | arxiv-cs.AI | 2024-11-13 |
| 845 | TRACE: Transformer-based Risk Assessment for Clinical Evaluation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present TRACE (Transformer-based Risk Assessment for Clinical Evaluation), a novel method for clinical risk assessment based on clinical data, leveraging the self-attention mechanism for enhanced feature interaction and result interpretation. |
Dionysis Christopoulos; Sotiris Spanos; Valsamis Ntouskos; Konstantinos Karantzalos; | arxiv-cs.CV | 2024-11-13 |
| 846 | Circuit Complexity Bounds for RoPE-based Transformer Architecture IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we establish a circuit complexity bound for Transformers with $\mathsf{RoPE}$ attention. |
BO CHEN et. al. | arxiv-cs.LG | 2024-11-12 |
| 847 | Derivational Morphology Reveals Analogical Generalization in Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce a new method for investigating linguistic generalization in LLMs: focusing on GPT-J, we fit cognitive models that instantiate rule-based and analogical learning to the LLM training data and compare their predictions on a set of nonce adjectives with those of the LLM, allowing us to draw direct conclusions regarding underlying mechanisms. |
Valentin Hofmann; Leonie Weissweiler; David Mortensen; Hinrich Schütze; Janet Pierrehumbert; | arxiv-cs.CL | 2024-11-12 |
| 848 | Responsible AI in Construction Safety: Systematic Evaluation of Large Language Models and Prompt Engineering Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Using 385 questions spanning seven safety knowledge areas, the study analyzes the models’ accuracy, consistency, and reliability. |
Farouq Sammour; Jia Xu; Xi Wang; Mo Hu; Zhenyu Zhang; | arxiv-cs.AI | 2024-11-12 |
| 849 | Split and Merge: Aligning Position Biases in LLM-based Evaluators IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, LLM-based evaluators exhibit position bias, or inconsistency, when used to evaluate candidate answers in pairwise comparisons, favoring either the first or second answer regardless of content. To address this limitation, we propose PORTIA, an alignment-based system designed to mimic human comparison strategies to calibrate position bias in a lightweight yet effective manner. |
ZONGJIE LI et. al. | emnlp | 2024-11-11 |
| 850 | Fine-Grained Detection of Solidarity for Women and Migrants in 155 Years of German Parliamentary Debates Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this study, we investigate the frequency of (anti-)solidarity towards women and migrants in German parliamentary debates between 1867 and 2022. |
AIDA KOSTIKOVA et. al. | emnlp | 2024-11-11 |
| 851 | Advancing Semantic Textual Similarity Modeling: A Regression Framework with Translated ReLU and Smooth K2 Loss Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Despite its efficiency, Sentence-BERT tackles STS tasks from a classification perspective, overlooking the progressive nature of semantic relationships, which results in suboptimal performance. To bridge this gap, this paper presents an innovative regression framework and proposes two simple yet effective loss functions: Translated ReLU and Smooth K2 Loss. |
Bowen Zhang; Chunping Li; | emnlp | 2024-11-11 |
| 852 | Linguistic Bias in ChatGPT: Language Models Reinforce Dialect Discrimination IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present a large-scale study of linguistic bias exhibited by ChatGPT covering ten dialects of English (Standard American English, Standard British English, and eight widely spoken non-standard varieties from around the world). |
EVE FLEISIG et. al. | emnlp | 2024-11-11 |
| 853 | Can LLMs Replace Neil DeGrasse Tyson? Evaluating The Reliability of LLMs As Science Communicators Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we focus on evaluating the reliability of current LLMs as science communicators. |
Prasoon Bajpai; Niladri Chatterjee; Subhabrata Dutta; Tanmoy Chakraborty; | emnlp | 2024-11-11 |
| 854 | A Unified Multi-Task Learning Architecture for Hate Detection Leveraging User-Based Information Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Most existing hate speech detection solutions have utilized the features by treating each post as an isolated input instance for the classification. This paper addresses this issue by introducing a unique model that improves hate speech identification for the English language by utilising intra-user and inter-user-based information. |
Prashant Kapil; Asif Ekbal; | arxiv-cs.CL | 2024-11-11 |
| 855 | Comparing A BERT Classifier and A GPT Classifier for Detecting Connective Language Across Multiple Social Media Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study presents an approach for detecting connective language-defined as language that facilitates engagement, understanding, and conversation-from social media discussions. |
Josephine Lukito; Bin Chen; Gina M. Masullo; Natalie Jomini Stroud; | emnlp | 2024-11-11 |
| 856 | BudgetMLAgent: A Cost-Effective LLM Multi-Agent System for Automating Machine Learning Tasks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: With the motivation of developing a cost-efficient LLM based solution for solving ML tasks, we propose an LLM Multi-Agent based system which leverages combination of experts using profiling, efficient retrieval of past observations, LLM cascades, and ask-the-expert calls. |
Shubham Gandhi; Manasi Patwardhan; Lovekesh Vig; Gautam Shroff; | arxiv-cs.MA | 2024-11-11 |
| 857 | DA3: A Distribution-Aware Adversarial Attack Against Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Consequently, they are easy to detect using straightforward detection methods, diminishing the efficacy of such attacks. To address this issue, we propose a Distribution-Aware Adversarial Attack (DA3) method. |
Yibo Wang; Xiangjue Dong; James Caverlee; Philip S. Yu; | emnlp | 2024-11-11 |
| 858 | SparseGrad: A Selective Method for Efficient Fine-tuning of MLP Layers Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a new selective PEFT method, namely SparseGrad, that performs well on MLP blocks. |
VIKTORIIA A. CHEKALINA et. al. | emnlp | 2024-11-11 |
| 859 | SYNFAC-EDIT: Synthetic Imitation Edit Feedback for Factual Alignment in Clinical Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: So in this work, we leverage 100B+ GPT variants to act as synthetic feedback experts offering expert-level edit feedback, that is used to reduce hallucinations and align weaker (<10B parameter) LLMs with medical facts using two distinct alignment algorithms (DPO & SALT), endeavoring to narrow the divide between AI-generated content and factual accuracy. |
PRAKAMYA MISHRA et. al. | emnlp | 2024-11-11 |
| 860 | Generalizing Clinical De-identification Models By Privacy-safe Data Augmentation Using GPT-4 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Additionally, labeling standards and the formats of patient records vary across different institutions. Our study addresses these issues by exploiting GPT-4 for data augmentation through one-shot and zero-shot prompts. |
Woojin Kim; Sungeun Hahm; Jaejin Lee; | emnlp | 2024-11-11 |
| 861 | MTLS: Making Texts Into Linguistic Symbols Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we shift the focus to the symbolic properties and introduce MTLS: a pre-training method to improve the multilingual capability of models by Making Texts into Linguistic Symbols. |
Wenlong Fei; Xiaohua Wang; Min Hu; Qingyu Zhang; Hongbo Li; | emnlp | 2024-11-11 |
| 862 | White-Box Diffusion Transformer for Single-cell RNA-seq Generation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, the process of data acquisition is often constrained by high cost and limited sample availability. To overcome these limitations, we propose a hybrid model based on Diffusion model and White-Box transformer that aims to generate synthetic and biologically plausible scRNA-seq data. |
Zhuorui Cui; Shengze Dong; Ding Liu; | arxiv-cs.LG | 2024-11-11 |
| 863 | TempCharBERT: Keystroke Dynamics for Continuous Access Control Based on Pre-trained Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: A particular interest lies on keystroke dynamics (KD), which refers to the task of recognizing individuals’ identity based on their unique typing style. In this work, we propose the use of pre-trained language models (PLMs) to recognize such patterns. |
Matheus Simão; Fabiano Prado; Omar Abdul Wahab; Anderson Avila; | arxiv-cs.CR | 2024-11-11 |
| 864 | Annotation Alignment: Comparing LLM and Human Annotations of Conversational Safety Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We show that larger datasets are needed to resolve whether GPT-4 exhibits disparities in how well it correlates with different demographic groups. |
Rajiv Movva; Pang Wei Koh; Emma Pierson; | emnlp | 2024-11-11 |
| 865 | TreeCoders: Trees of Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce TreeCoders, a novel family of transformer trees. |
Pierre Colonna D’Istria; Abdulrahman Altahhan; | arxiv-cs.CL | 2024-11-11 |
| 866 | On The Reliability of Psychological Scales on Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Our study aims to determine the reliability of applying personality assessments to LLMs, explicitly investigating whether LLMs demonstrate consistent personality traits. |
JEN-TSE HUANG et. al. | emnlp | 2024-11-11 |
| 867 | GPT Vs RETRO: Exploring The Intersection of Retrieval and Parameter-Efficient Fine-Tuning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we apply PEFT methods (P-tuning, Adapters, and LoRA) to a modified Retrieval-Enhanced Transformer (RETRO) and a baseline GPT model across several sizes, ranging from 823 million to 48 billion parameters. |
Aleksander Ficek; Jiaqi Zeng; Oleksii Kuchaiev; | emnlp | 2024-11-11 |
| 868 | On Training Data Influence of GPT Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper presents GPTfluence, a novel approach that leverages a featurized simulation to assess the impact of training examples on the training dynamics of GPT models. |
YEKUN CHAI et. al. | emnlp | 2024-11-11 |
| 869 | MaLei at The PLABA Track of TREC 2024: RoBERTa for Term Replacement — LLaMA3.1 and GPT-4o for Complete Abstract Adaptation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In task one (term replacement), we applied fine-tuned ReBERTa-Base models to identify and classify the difficult terms, jargon, and acronyms in the biomedical abstracts and reported the F1 score (Task 1A and 1B). |
Zhidong Ling; Zihao Li; Pablo Romero; Lifeng Han; Goran Nenadic; | arxiv-cs.CL | 2024-11-11 |
| 870 | DAMRO: Dive Into The Attention Mechanism of LVLM to Reduce Object Hallucination Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To address the issue, we propose DAMRO, a novel training-free strategy that **D**ive into **A**ttention **M**echanism of LVLM to **R**educe **O**bject Hallucination. |
Xuan Gong; Tianshi Ming; Xinpeng Wang; Zhihua Wei; | emnlp | 2024-11-11 |
| 871 | Unraveling The Gradient Descent Dynamics of Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: While the Transformer architecture has achieved remarkable success across various domains, a thorough theoretical foundation explaining its optimization dynamics is yet to be fully developed. In this study, we aim to bridge this understanding gap by answering the following two core questions: (1) Which types of Transformer architectures allow Gradient Descent (GD) to achieve guaranteed convergence? |
Bingqing Song; Boran Han; Shuai Zhang; Jie Ding; Mingyi Hong; | arxiv-cs.LG | 2024-11-11 |
| 872 | ConvMixFormer- A Resource-efficient Convolution Mixer for Transformer-based Dynamic Hand Gesture Recognition Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Transformer models have demonstrated remarkable success in many domains such as natural language processing (NLP) and computer vision. |
Mallika Garg; Debashis Ghosh; Pyari Mohan Pradhan; | arxiv-cs.CV | 2024-11-11 |
| 873 | Knowledge Graph Enhanced Large Language Model Editing IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, existing editing methods struggle to track and incorporate changes in knowledge associated with edits, which limits the generalization ability of post-edit LLMs in processing edited knowledge. To tackle these problems, we propose a novel model editing method that leverages knowledge graphs for enhancing LLM editing, namely GLAME. |
MENGQI ZHANG et. al. | emnlp | 2024-11-11 |
| 874 | Still Not Quite There! Evaluating Large Language Models for Comorbid Mental Health Diagnosis Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we introduce ANGST, a novel, first of its kind benchmark for depression-anxiety comorbidity classification from social media posts. |
AMEY HENGLE et. al. | emnlp | 2024-11-11 |
| 875 | Towards Interpretable Sequence Continuation: Analyzing Shared Circuits in Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We extend this research by analyzing and comparing circuits for similar sequence continuation tasks, which include increasing sequences of Arabic numerals, number words, and months. |
Michael Lan; Philip Torr; Fazl Barez; | emnlp | 2024-11-11 |
| 876 | Will LLMs Replace The Encoder-Only Models in Temporal Relation Classification? Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we investigate LLMs’ performance and decision process in the Temporal Relation Classification task. |
Gabriel Roccabruna; Massimo Rizzoli; Giuseppe Riccardi; | emnlp | 2024-11-11 |
| 877 | Leveraging Pre-trained Language Models for Linguistic Analysis: A Case of Argument Structure Constructions Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study evaluates the effectiveness of pre-trained language models in identifying argument structure constructions, important for modeling both first and second language learning. |
Hakyung Sung; Kristopher Kyle; | emnlp | 2024-11-11 |
| 878 | BiasWipe: Mitigating Unintended Bias in Text Classifiers Through Model Interpretability Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we present a robust and generalizable technique BiasWipe to mitigate unintended bias in language models. |
Mamta Mamta; Rishikant Chigrupaatii; Asif Ekbal; | emnlp | 2024-11-11 |
| 879 | FOOL ME IF YOU CAN! An Adversarial Dataset to Investigate The Robustness of LMs in Word Sense Disambiguation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, these models still struggle with recognizing semantic boundaries and often misclassify homonyms in adversarial context. Therefore, we propose FOOL: FOur-fold Obscure Lexical, a new coarse-grained WSD dataset, which includes four different test sets designed to assess the robustness of language models in WSD tasks. |
MOHAMAD BALLOUT et. al. | emnlp | 2024-11-11 |
| 880 | Reconstruct Your Previous Conversations! Comprehensively Investigating Privacy Leakage Risks in Conversations with GPT Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce a straightforward yet potent Conversation Reconstruction Attack. |
Junjie Chu; Zeyang Sha; Michael Backes; Yang Zhang; | emnlp | 2024-11-11 |
| 881 | Foundational Autoraters: Taming Large Language Models for Better Automatic Evaluation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: As large language models (LLMs) evolve, evaluating their output reliably becomes increasingly difficult due to the high cost of human evaluation. To address this, we introduce FLAMe, a family of Foundational Large Autorater Models. |
TU VU et. al. | emnlp | 2024-11-11 |
| 882 | Using Language Models to Disambiguate Lexical Choices in Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We work with native speakers of nine languages to create DTAiLS, a dataset of 1,377 sentence pairs that exhibit cross-lingual concept variation when translating from English. |
Josh Barua; Sanjay Subramanian; Kayo Yin; Alane Suhr; | emnlp | 2024-11-11 |
| 883 | Evaluating ChatGPT-3.5 Efficiency in Solving Coding Problems of Different Complexity Levels: An Empirical Analysis Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We assess the performance of ChatGPT’s GPT-3.5-turbo model on LeetCode, a popular platform with algorithmic coding challenges for technical interview practice, across three difficulty levels: easy, medium, and hard. |
Minda Li; Bhaskar Krishnamachari; | arxiv-cs.SE | 2024-11-11 |
| 884 | High-Fidelity Cellular Network Control-Plane Traffic Generation Without Domain Knowledge Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we study the feasibility of developing a high-fidelity MCN control plane traffic generator by leveraging generative ML models. |
Z. Jonny Kong; Nathan Hu; Y. Charlie Hu; Jiayi Meng; Yaron Koral; | arxiv-cs.NI | 2024-11-11 |
| 885 | Is Child-Directed Speech Effective Training Data for Language Models? Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: What are the features of the data they receive, and how do these features support language modeling objectives? To investigate this question, we train GPT-2 and RoBERTa models on 29M words of English child-directed speech and a new matched, synthetic dataset (TinyDialogues), comparing to OpenSubtitles, Wikipedia, and a heterogeneous blend of datasets from the BabyLM challenge. |
Steven Y. Feng; Noah Goodman; Michael Frank; | emnlp | 2024-11-11 |
| 886 | Pron Vs Prompt: Can Large Language Models Already Challenge A World-Class Fiction Author at Creative Text Writing? Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Are LLMs ready to compete in creative writing skills with a top (rather than average) novelist? To provide an initial answer for this question, we have carried out a contest … |
Guillermo Marco; Julio Gonzalo; M.Teresa Mateo-Girona; Ram�n Del Castillo Santos; | emnlp | 2024-11-11 |
| 887 | GPT-4 Jailbreaks Itself with Near-Perfect Success Using Self-Explanation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce Iterative Refinement Induced Self-Jailbreak (IRIS), a novel approach that leverages the reflective capabilities of LLMs for jailbreaking with only black-box access. |
Govind Ramesh; Yao Dou; Wei Xu; | emnlp | 2024-11-11 |
| 888 | Surveying The Dead Minds: Historical-Psychological Text Analysis with Contextualized Construct Representation (CCR) for Classical Chinese Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we develop a pipeline for historical-psychological text analysis in classical Chinese. |
Yuqi Chen; Sixuan Li; Ying Li; Mohammad Atari; | emnlp | 2024-11-11 |
| 889 | Universal Response and Emergence of Induction in LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: By applying our method, we observe signatures of induction behavior within the residual stream of Gemma-2-2B, Llama-3.2-3B, and GPT-2-XL. Across all models, we find that these induction signatures gradually emerge within intermediate layers and identify the relevant model sections composing this behavior. |
Niclas Luick; | arxiv-cs.LG | 2024-11-11 |
| 890 | Subword Segmentation in LLMs: Looking at Inflection and Consistency Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We study two criteria: (i) adherence to morpheme boundaries and (ii) the segmentation consistency of the different inflected forms of a lemma. |
Marion Di Marco; Alexander Fraser; | emnlp | 2024-11-11 |
| 891 | Evaluating Psychological Safety of Large Language Models IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we designed unbiased prompts to systematically evaluate the psychological safety of large language models (LLMs). |
Xingxuan Li; Yutong Li; Lin Qiu; Shafiq Joty; Lidong Bing; | emnlp | 2024-11-11 |
| 892 | MiniCheck: Efficient Fact-Checking of LLMs on Grounding Documents IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we show how to build small fact-checking models that have GPT-4-level performance but for 400x lower cost. |
Liyan Tang; Philippe Laban; Greg Durrett; | emnlp | 2024-11-11 |
| 893 | Ambient AI Scribing Support: Comparing The Performance of Specialized AI Agentic Architecture to Leading Foundational Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study compares Sporo Health’s AI Scribe, a proprietary model fine-tuned for medical scribing, with various LLMs (GPT-4o, GPT-3.5, Gemma-9B, and Llama-3.2-3B) in clinical documentation. |
Chanseo Lee; Sonu Kumar; Kimon A. Vogt; Sam Meraj; | arxiv-cs.AI | 2024-11-10 |
| 894 | LProtector: An LLM-driven Vulnerability Detection System Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents LProtector, an automated vulnerability detection system for C/C++ codebases driven by the large language model (LLM) GPT-4o and Retrieval-Augmented Generation (RAG). |
ZE SHENG et. al. | arxiv-cs.CR | 2024-11-10 |
| 895 | Prompt-Efficient Fine-Tuning for GPT-like Deep Models to Reduce Hallucination and to Improve Reproducibility in Scientific Text Generation Using Stochastic Optimisation Techniques Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This thesis introduces a Parameter-Efficient Fine-Tuning (PEFT) approach tailored for GPT-like models, aiming to mitigate hallucinations and enhance reproducibility, particularly in the computational domain of mass spectrometry. |
Daniil Sulimov; | arxiv-cs.CL | 2024-11-10 |
| 896 | Golden Touchstone: A Comprehensive Bilingual Benchmark for Evaluating Financial Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, existing finance benchmarks often suffer from limited language and task coverage, as well as challenges such as low-quality datasets and inadequate adaptability for LLM evaluation. To address these limitations, we propose Golden Touchstone, the first comprehensive bilingual benchmark for financial LLMs, which incorporates representative datasets from both Chinese and English across eight core financial NLP tasks. |
XIAOJUN WU et. al. | arxiv-cs.CL | 2024-11-09 |
| 897 | AI’s Spatial Intelligence: Evaluating AI’s Understanding of Spatial Transformations in PSVT:R and Augmented Reality Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Recent studies show Artificial Intelligence (AI) with language and vision capabilities still face limitations in spatial reasoning. In this paper, we have studied generative AI’s spatial capabilities of understanding rotations of objects utilizing its image and language processing features. |
Uttamasha Monjoree; Wei Yan; | arxiv-cs.AI | 2024-11-09 |
| 898 | High Entropy Alloy Property Predictions Using Transformer-based Language Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study introduces a language transformer-based machine learning model to predict key mechanical properties of high-entropy alloys (HEAs), addressing the challenges due to their complex, multi-principal element compositions and limited experimental data. |
Spyros Kamnis; Konstantinos Delibasis; | arxiv-cs.CE | 2024-11-07 |
| 899 | FineTuneBench: How Well Do Commercial Fine-tuning APIs Infuse Knowledge Into LLMs? Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this study, we introduce FineTuneBench, an evaluation framework and dataset for understanding how well commercial fine-tuning APIs can successfully learn new and updated knowledge. |
Eric Wu; Kevin Wu; James Zou; | arxiv-cs.CL | 2024-11-07 |
| 900 | Lightning IR: Straightforward Fine-tuning and Inference of Transformer-based Language Models for Information Retrieval Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce Lightning IR, an easy-to-use PyTorch Lightning-based framework for applying transformer-based language models in retrieval scenarios. |
Ferdinand Schlatt; Maik Fröbe; Matthias Hagen; | arxiv-cs.IR | 2024-11-07 |
| 901 | Evaluating GPT-4 at Grading Handwritten Solutions in Math Exams Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we leverage state-of-the-art multi-modal AI models, in particular GPT-4o, to automatically grade handwritten responses to college-level math exams. |
Adriana Caraeni; Alexander Scarlatos; Andrew Lan; | arxiv-cs.CY | 2024-11-07 |
| 902 | GPT Semantic Cache: Reducing LLM Costs and Latency Via Semantic Embedding Caching Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce GPT Semantic Cache, a method that leverages semantic caching of query embeddings in in-memory storage (Redis). |
Sajal Regmi; Chetan Phakami Pun; | arxiv-cs.LG | 2024-11-07 |
| 903 | A Comparative Study of Recent Large Language Models on Generating Hospital Discharge Summaries for Lung Cancer Patients Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This research aims to explore how LLMs can alleviate the burden of manual summarization, streamline workflow efficiencies, and support informed decision-making in healthcare settings. |
YIMING LI et. al. | arxiv-cs.CL | 2024-11-06 |
| 904 | On-Device Emoji Classifier Trained with GPT-based Data Augmentation for A Mobile Keyboard Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes an on-device emoji classifier based on MobileBert with reasonable memory and latency requirements for SwiftKey. |
Hossam Amer; Joe Osborne; Michael Zaki; Mohamed Afify; | arxiv-cs.CL | 2024-11-06 |
| 905 | Understanding The Effects of Human-written Paraphrases in LLM-generated Text Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this study, we devise a new data collection strategy to collect Human & LLM Paraphrase Collection (HLPC), a first-of-its-kind dataset that incorporates human-written texts and paraphrases, as well as LLM-generated texts and paraphrases. |
Hiu Ting Lau; Arkaitz Zubiaga; | arxiv-cs.CL | 2024-11-06 |
| 906 | Towards Scalable Automated Grading: Leveraging Large Language Models for Conceptual Question Evaluation in Engineering Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study explores the feasibility of using large language models (LLMs), specifically GPT-4o (ChatGPT), for automated grading of conceptual questions in an undergraduate Mechanical Engineering course. |
RUJUN GAO et. al. | arxiv-cs.CY | 2024-11-05 |
| 907 | Enhancing Transformer Training Efficiency with Dynamic Dropout Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce Dynamic Dropout, a novel regularization technique designed to enhance the training efficiency of Transformer models by dynamically adjusting the dropout rate based on training epochs or validation loss improvements. |
Hanrui Yan; Dan Shao; | arxiv-cs.LG | 2024-11-05 |
| 908 | From Medprompt to O1: Exploration of Run-Time Strategies for Medical Challenge Problems and Beyond Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Following on the Medprompt study with GPT-4, we systematically evaluate the o1-preview model across various medical benchmarks. |
HARSHA NORI et. al. | arxiv-cs.CL | 2024-11-05 |
| 909 | Automatic Generation of Question Hints for Mathematics Problems Using Large Language Models in Educational Technology Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present here the study of several dimensions: 1) identifying error patterns made by simulated students on secondary-level math exercises; 2) developing various prompts for GPT-4o as a teacher and evaluating their effectiveness in generating hints that enable simulated students to self-correct; and 3) testing the best-performing prompts, based on their ability to produce relevant hints and facilitate error correction, with Llama-3-8B-Instruct as the teacher, allowing for a performance comparison with GPT-4o. |
Junior Cedric Tonga; Benjamin Clement; Pierre-Yves Oudeyer; | arxiv-cs.CL | 2024-11-05 |
| 910 | Seq-VCR: Preventing Collapse in Intermediate Transformer Representations for Enhanced Reasoning Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we identify representation collapse in the model’s intermediate layers as a key factor limiting their reasoning capabilities. |
MD RIFAT AREFIN et. al. | arxiv-cs.LG | 2024-11-04 |
| 911 | Ask, and It Shall Be Given: Turing Completeness of Prompting Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Since the success of GPT, large language models (LLMs) have been revolutionizing machine learning and have initiated the so-called LLM prompting paradigm. In the era of LLMs, … |
Ruizhong Qiu; Zhe Xu; Wenxuan Bao; Hanghang Tong; | ArXiv | 2024-11-04 |
| 912 | Advancements and Limitations of LLMs in Replicating Human Color-word Associations Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We compared multiple generations of LLMs (from GPT-3 to GPT-4o) against human color-word associations using data collected from over 10,000 Japanese participants, involving 17 colors and 80 words (10 word from eight categories) in Japanese. |
Makoto Fukushima; Shusuke Eshita; Hiroshige Fukuhara; | arxiv-cs.CL | 2024-11-04 |
| 913 | Wave Network: An Ultra-Small Language Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose an innovative token representation and update method in a new ultra-small language model: the Wave network. |
Xin Zhang; Victor S. Sheng; | arxiv-cs.CL | 2024-11-04 |
| 914 | Enriching Tabular Data with Contextual LLM Embeddings: A Comprehensive Ablation Study for Ensemble Classifiers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Leveraging advancements in natural language processing, this study presents a systematic approach to enrich tabular datasets with features derived from large language model embeddings. |
Gjergji Kasneci; Enkelejda Kasneci; | arxiv-cs.LG | 2024-11-03 |
| 915 | Can Large Language Model Predict Employee Attrition? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Machine learning (ML) advancements offer more scalable and accurate solutions, but large language models (LLMs) introduce new potential in human resource management by interpreting nuanced employee communication and detecting subtle turnover cues. |
Xiaoye Ma; Weiheng Liu; Changyi Zhao; Liliya R. Tukhvatulina; | arxiv-cs.LG | 2024-11-02 |
| 916 | Lingma SWE-GPT: An Open Development-Process-Centric Language Model for Automated Software Improvement Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Consequently, we introduce the Lingma SWE-GPT series, comprising Lingma SWE-GPT 7B and 72B. |
YINGWEI MA et. al. | arxiv-cs.SE | 2024-11-01 |
| 917 | Online Semi-Supervised Transformer for Resilient Vehicle GNSS/INS Navigation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The Inertial Navigation Systems (INS) and Global Navigation Satellite Systems (GNSS) integrated navigation system is widely employed for vehicular positioning. However, obstacles … |
HAOWEN WANG et. al. | IEEE Transactions on Vehicular Technology | 2024-11-01 |
| 918 | GameGen-X: Interactive Open-world Game Video Generation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce GameGen-X, the first diffusion transformer model specifically designed for both generating and interactively controlling open-world game videos. |
Haoxuan Che; Xuanhua He; Quande Liu; Cheng Jin; Hao Chen; | arxiv-cs.CV | 2024-11-01 |
| 919 | LLMs: A Game-Changer for Software Engineers? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Through a critical analysis of technical strengths, limitations, real-world case studies, and future research directions, this paper argues that LLMs are not just reshaping how software is developed but are redefining the role of developers. |
Md Asraful Haque; | arxiv-cs.SE | 2024-11-01 |
| 920 | Infant Agent: A Tool-Integrated, Logic-Driven Agent with Cost-Effective API Usage Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: \textbf{\uppercase\expandafter{\romannumeral 2}}: They remain \textbf{challenged in reasoning through complex logic problems}. To address these challenges, we developed the \textsc{Infant Agent}, integrating task-aware functions, operators, a hierarchical management system, and a memory retrieval mechanism. |
BIN LEI et. al. | arxiv-cs.AI | 2024-11-01 |
| 921 | A Lightweight CNN-Transformer Network for Pixel-based Crop Mapping Using Time-series Sentinel-2 Imagery Related Papers Related Patents Related Grants Related Venues Related Experts View |
YUMIAO WANG et. al. | Comput. Electron. Agric. | 2024-11-01 |
| 922 | Transformer-CNN for Small Image Object Detection Related Papers Related Patents Related Grants Related Venues Related Experts View |
Yan-Lin Chen; Chun-Liang Lin; Yu-Chen Lin; Tzu-Chun Chen; | Signal Process. Image Commun. | 2024-11-01 |
| 923 | Aerial Flood Scene Classification Using Fine-Tuned Attention-based Architecture for Flood-Prone Countries in South Asia Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: For the classification, we propose a fine-tuned Compact Convolutional Transformer (CCT) based approach and some other cutting-edge transformer-based and Convolutional Neural Network-based architectures (CNN). |
IBNE HASSAN et. al. | arxiv-cs.CV | 2024-10-31 |
| 924 | Exploring Vision Language Models for Facial Attribute Recognition: Emotion, Race, Gender, and Age Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose to utilize vision language models (VLMs) such as generative pre-trained transformer (GPT), GEMINI, large language and vision assistant (LLAVA), PaliGemma, and Microsoft Florence2 to recognize facial attributes such as race, gender, age, and emotion from images with human faces. |
Nouar AlDahoul; Myles Joshua Toledo Tan; Harishwar Reddy Kasireddy; Yasir Zaki; | arxiv-cs.CV | 2024-10-31 |
| 925 | GPT or BERT: Why Not Both? Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present a simple way to merge masked language modeling with causal language modeling. |
Lucas Georges Gabriel Charpentier; David Samuel; | arxiv-cs.CL | 2024-10-31 |
| 926 | IO Transformer: Evaluating SwinV2-Based Reward Models for Computer Vision Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper examines SwinV2-based reward models, called the Input-Output Transformer (IO Transformer) and the Output Transformer. |
Maxwell Meyer; Jack Spruyt; | arxiv-cs.CV | 2024-10-31 |
| 927 | GPT for Games: An Updated Scoping Review (2020-2024) Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This review aims to illustrate the state of the art in innovative GPT applications in games, offering a foundation to enrich game development and enhance player experiences through cutting-edge AI innovations. |
Daijin Yang; Erica Kleinman; Casper Harteveld; | arxiv-cs.AI | 2024-10-31 |
| 928 | Handwriting Recognition in Historical Documents with Multimodal LLM Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, I evaluate the accuracy of handwritten document transcriptions generated by Gemini against the current state of the art Transformer based methods. |
Lucian Li; | arxiv-cs.CV | 2024-10-31 |
| 929 | Desert Camels and Oil Sheikhs: Arab-Centric Red Teaming of Frontier LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Large language models (LLMs) are widely used but raise ethical concerns due to embedded social biases. |
MUHAMMED SAEED et. al. | arxiv-cs.CL | 2024-10-31 |
| 930 | EDT: An Efficient Diffusion Transformer Framework Inspired By Human-like Sketching Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To reduce the computation budget of transformer-based DPMs, this work proposes the Efficient Diffusion Transformer (EDT) framework. |
Xinwang Chen; Ning Liu; Yichen Zhu; Feifei Feng; Jian Tang; | arxiv-cs.CV | 2024-10-31 |
| 931 | An Empirical Analysis of GPT-4V’s Performance on Fashion Aesthetic Evaluation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Fashion aesthetic evaluation is the task of estimating how well the outfits worn by individuals in images suit them. In this work, we examine the zero-shot performance of GPT-4V on this task for the first time. |
YUKI HIRAKAWA et. al. | arxiv-cs.CV | 2024-10-31 |
| 932 | A Comprehensive Study on Quantization Techniques for Large Language Models Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Large Language Models (LLMs) have been extensively researched and used in both academia and industry since the rise in popularity of the Transformer model, which demonstrates … |
Jiedong Lang; Zhehao Guo; Shuyu Huang; | ArXiv | 2024-10-30 |
| 933 | LoFLAT: Local Feature Matching Using Focused Linear Attention Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In order to enhance representations of attention mechanisms while preserving low computational complexity, we propose the LoFLAT, a novel Local Feature matching using Focused Linear Attention Transformer in this paper. |
Naijian Cao; Renjie He; Yuchao Dai; Mingyi He; | arxiv-cs.CV | 2024-10-30 |
| 934 | ETO:Efficient Transformer-based Local Feature Matching By Organizing Multiple Homography Hypotheses Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose an efficient transformer-based network architecture for local feature matching. |
JUNJIE NI et. al. | arxiv-cs.CV | 2024-10-30 |
| 935 | Automated Personnel Selection for Software Engineers Using LLM-Based Profile Evaluation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work presents a fresh dataset and technique as well as shows how transformer models could improve recruiting procedures. |
Ahmed Akib Jawad Karim; Shahria Hoque; Md. Golam Rabiul Alam; Md. Zia Uddin; | arxiv-cs.SE | 2024-10-30 |
| 936 | EvoCodeBench: An Evolving Code Generation Benchmark with Domain-Specific Evaluations Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The former hurts the fairness of benchmarks, and the latter hinders practitioners from selecting superior LLMs for specific programming domains. To address these two limitations, we propose a new benchmark – EvoCodeBench, which has the following advances: (1) Evolving data. |
JIA LI et. al. | arxiv-cs.CL | 2024-10-30 |
| 937 | ProTransformer: Robustify Transformers Via Plug-and-Play Paradigm Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce a novel robust attention mechanism designed to enhance the resilience of transformer-based architectures. |
Zhichao Hou; Weizhi Gao; Yuchen Shen; Feiyi Wang; Xiaorui Liu; | arxiv-cs.LG | 2024-10-30 |
| 938 | Attention Speaks Volumes: Localizing and Mitigating Bias in Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We explore the internal mechanisms of how bias emerges in large language models (LLMs) when provided with ambiguous comparative prompts: inputs that compare or enforce choosing between two or more entities without providing clear context for preference. |
Rishabh Adiga; Besmira Nushi; Varun Chandrasekaran; | arxiv-cs.CL | 2024-10-29 |
| 939 | AmpleGCG-Plus: A Strong Generative Model of Adversarial Suffixes to Jailbreak LLMs with Higher Success Rates in Fewer Attempts Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Recent work, AmpleGCG~\citep{liao2024amplegcg}, demonstrates that a generative model can quickly produce numerous customizable gibberish adversarial suffixes for any harmful query, exposing a range of alignment gaps in out-of-distribution (OOD) language spaces. To bring more attention to this area, we introduce AmpleGCG-Plus, an enhanced version that achieves better performance in fewer attempts. |
Vishal Kumar; Zeyi Liao; Jaylen Jones; Huan Sun; | arxiv-cs.CL | 2024-10-29 |
| 940 | GPT-4o Reads The Mind in The Eyes Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Using two versions of a widely used theory of mind test, the Reading the Mind in Eyes Test and the Multiracial Reading the Mind in the Eyes Test, we found that GPT-4o outperformed humans in interpreting mental states from upright faces but underperformed humans when faces were inverted. |
JAMES W. A. STRACHAN et. al. | arxiv-cs.HC | 2024-10-29 |
| 941 | Is GPT-4 Less Politically Biased Than GPT-3.5? A Renewed Investigation of ChatGPT’s Political Biases Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work investigates the political biases and personality traits of ChatGPT, specifically comparing GPT-3.5 to GPT-4. |
Erik Weber; Jérôme Rutinowski; Niklas Jost; Markus Pauly; | arxiv-cs.CL | 2024-10-28 |
| 942 | Sequential Choice in Ordered Bundles Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We evaluate several predictive models, including two custom Transformers using decoder-only and encoder-decoder architectures, fine-tuned GPT-3, a custom LSTM model, a reinforcement learning model, two Markov models, and a zero-order model. |
Rajeev Kohli; Kriste Krstovski; Hengyu Kuang; Hengxu Lin; | arxiv-cs.LG | 2024-10-28 |
| 943 | A Simple Yet Effective Corpus Construction Framework for Indonesian Grammatical Error Correction Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: How to efficiently construct high-quality evaluation corpora for GEC in low-resource languages has become a significant challenge. To fill these gaps, in this paper, we present a framework for constructing GEC corpora. |
NANKAI LIN et. al. | arxiv-cs.CL | 2024-10-28 |
| 944 | 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 SepMamba, a U-Net-based architecture composed primarily of bidirectional Mamba layers. |
THOR HØJHUS AVENSTRUP et. al. | arxiv-cs.SD | 2024-10-28 |
| 945 | KD-LoRA: A Hybrid Approach to Efficient Fine-Tuning with LoRA and Knowledge Distillation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we present KD-LoRA, a novel fine-tuning method that combines LoRA with KD. |
Rambod Azimi; Rishav Rishav; Marek Teichmann; Samira Ebrahimi Kahou; | arxiv-cs.CL | 2024-10-28 |
| 946 | Deep Learning for Medical Text Processing: BERT Model Fine-Tuning and Comparative Study Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes a medical literature summary generation method based on the BERT model to address the challenges brought by the current explosion of medical information. |
JIACHENG HU et. al. | arxiv-cs.CL | 2024-10-28 |
| 947 | MultiTok: Variable-Length Tokenization for Efficient LLMs Adapted from LZW Compression Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, current methodologies to train such LLMs require extensive resources including but not limited to large amounts of data, expensive machinery, and lengthy training. To solve this problem, this paper proposes a new tokenization method inspired by universal Lempel-Ziv-Welch data compression that compresses repetitive phrases into multi-word tokens. |
Noel Elias; Homa Esfahanizadeh; Kaan Kale; Sriram Vishwanath; Muriel Medard; | arxiv-cs.CL | 2024-10-28 |
| 948 | UOttawa at LegalLens-2024: Transformer-based Classification Experiments Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper presents the methods used for LegalLens-2024 shared task, which focused on detecting legal violations within unstructured textual data and associating these violations with potentially affected individuals. |
Nima Meghdadi; Diana Inkpen; | arxiv-cs.CL | 2024-10-28 |
| 949 | Gender Bias in LLM-generated Interview Responses Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Our findings reveal that gender bias is consistent, and closely aligned with gender stereotypes and the dominance of jobs. Overall, this study contributes to the systematic examination of gender bias in LLM-generated interview responses, highlighting the need for a mindful approach to mitigate such biases in related applications. |
Haein Kong; Yongsu Ahn; Sangyub Lee; Yunho Maeng; | arxiv-cs.CL | 2024-10-28 |
| 950 | Exploring The Potential of Large Language Models for Red Teaming in Military Coalition Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This paper reports on an ongoing investigation comparing the performance of large language models (LLMs) in generating penetration test scripts for realistic red agents. The goal … |
ERIK ADLER et. al. | MILCOM 2024 – 2024 IEEE Military Communications Conference … | 2024-10-28 |
| 951 | Fine-tuned Large Language Models (LLMs): Improved Prompt Injection Attacks Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This project explores the security vulnerabilities in relation to prompt injection attacks. |
Md Abdur Rahman; Fan Wu; Alfredo Cuzzocrea; Sheikh Iqbal Ahamed; | arxiv-cs.CL | 2024-10-27 |
| 952 | SeisGPT: A Physics-Informed Data-Driven Large Model for Real-Time Seismic Response Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Traditional methods, which rely on complex finite element models often struggle with balancing computational efficiency and accuracy. To address this challenge, we introduce SeisGPT, a data-driven, large physics-informed model that leverages deep neural networks based on the Generative Pre-trained Transformer (GPT) architecture. |
SHIQIAO MENG et. al. | arxiv-cs.CE | 2024-10-26 |
| 953 | Notes on The Mathematical Structure of GPT LLM Architectures Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: An exposition of the mathematics underpinning the neural network architecture of a GPT-3-style LLM. … |
Spencer Becker-Kahn; | arxiv-cs.LG | 2024-10-25 |
| 954 | GPT-4o System Card IF:4 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: GPT-4o is an autoregressive omni model that accepts as input any combination of text, audio, image, and video, and generates any combination of text, audio, and image outputs. … |
OPENAI AARON HURST et. al. | ArXiv | 2024-10-25 |
| 955 | Understanding Ranking LLMs: A Mechanistic Analysis for Information Retrieval Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we investigate the internal mechanisms of state-of-the-art, fine-tuned LLMs for passage reranking. |
Tanya Chowdhury; Atharva Nijasure; James Allan; | arxiv-cs.IR | 2024-10-24 |
| 956 | Integrating Large Language Models with Internet of Things Applications Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper identifies and analyzes applications in which Large Language Models (LLMs) can make Internet of Things (IoT) networks more intelligent and responsive through three case studies from critical topics: DDoS attack detection, macroprogramming over IoT systems, and sensor data processing. |
Mingyu Zong; Arvin Hekmati; Michael Guastalla; Yiyi Li; Bhaskar Krishnamachari; | arxiv-cs.AI | 2024-10-24 |
| 957 | ADVLLM: Iterative Self-Tuning LLMs for Enhanced Jailbreaking Capabilities Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Moreover, it exhibits strong attacktransferability to closed-source models, achieving 99\% ASR on GPT-3.5 and 49\%ASR on GPT-4, despite being optimized solely on Llama3. Beyond improvingjailbreak ability, ADV-LLM provides valuable insights for future safetyalignment research through its ability to generate large datasets for studyingLLM safety. |
CHUNG-EN SUN et. al. | arxiv-cs.CL | 2024-10-24 |
| 958 | No Argument Left Behind: Overlapping Chunks for Faster Processing of Arbitrarily Long Legal Texts Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce uBERT, a hybrid model that combines Transformer and Recurrent Neural Network architectures to effectively handle long legal texts. |
ISRAEL FAMA et. al. | arxiv-cs.CL | 2024-10-24 |
| 959 | GPT-Signal: Generative AI for Semi-automated Feature Engineering in The Alpha Research Process Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: With the recent development of Generative Artificial Intelligence(Gen AI) and Large Language Models (LLMs), we present a novel way of leveraging GPT-4 to generate new return-predictive formulaic alphas, making alpha mining a semi-automated process, and saving time and energy for investors and traders. |
Yining Wang; Jinman Zhao; Yuri Lawryshyn; | arxiv-cs.CE | 2024-10-24 |
| 960 | OmniFlatten: An End-to-end GPT Model for Seamless Voice Conversation 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. | arxiv-cs.CL | 2024-10-23 |
| 961 | Striking A New Chord: Neural Networks in Music Information Dynamics Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Specifically, we compare LSTM, Transformer, and GPT models against a widely-used markov model to predict a chord event following a sequence of chords. |
Farshad Jafari; Claire Arthur; | arxiv-cs.IT | 2024-10-23 |
| 962 | An Eye for An AI: Evaluating GPT-4o’s Visual Perception Skills and Geometric Reasoning Skills Using Computer Graphics Questions Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We find that although GPT-4o exhibits great potential in solving questions with visual information independently, major limitations still exist to the accuracy and quality of the generated results. We propose several novel approaches for CG educators to incorporate GenAI into CG teaching despite these limitations. |
Tony Haoran Feng; Paul Denny; Burkhard C. Wünsche; Andrew Luxton-Reilly; Jacqueline Whalley; | arxiv-cs.AI | 2024-10-22 |
| 963 | Interpreting Affine Recurrence Learning in GPT-style Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In-context learning allows transformers to generalize during inference without modifying their weights, yet the precise operations driving this capability remain largely opaque. This paper presents an investigation into the mechanistic interpretability of these transformers, focusing specifically on their ability to learn and predict affine recurrences as an ICL task. |
Samarth Bhargav; Alexander Gu; | arxiv-cs.LG | 2024-10-22 |
| 964 | In Context Learning and Reasoning for Symbolic Regression with Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Here, we explore the potential of LLMs to perform symbolic regression — a machine-learning method for finding simple and accurate equations from datasets. |
Samiha Sharlin; Tyler R. Josephson; | arxiv-cs.CL | 2024-10-22 |
| 965 | Real-Time Email Phishing Detection Using A Custom DistilBERT Model Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This paper presents a real-time email phishing detection system that utilizes a custom DistilBERT model. The custom DistilBERT architecture incorporates dynamic threshold … |
Edafe Maxwell Damatie; A. Eleyan; Tarek Bejaoui; | 2024 International Symposium on Networks, Computers and … | 2024-10-22 |
| 966 | GeoCode-GPT: A Large Language Model for Geospatial Code Generation Tasks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Although large language models (LLMs) have demonstrated potential in code generation tasks, they often encounter issues such as refusal to code or hallucination in geospatial code generation due to a lack of domain-specific knowledge and code corpora. To address these challenges, this paper presents and open-sources the GeoCode-PT and GeoCode-SFT corpora, along with the GeoCode-Eval evaluation dataset. |
SHUYANG HOU et. al. | arxiv-cs.SE | 2024-10-22 |
| 967 | Using GPT Models for Qualitative and Quantitative News Analytics in The 2024 US Presidental Election Process Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The paper considers an approach of using Google Search API and GPT-4o model for qualitative and quantitative analyses of news through retrieval-augmented generation (RAG). |
Bohdan M. Pavlyshenko; | arxiv-cs.CL | 2024-10-21 |
| 968 | Exploring Pretraining Via Active Forgetting for Improving Cross Lingual Transfer for Decoder Language Models 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; | arxiv-cs.CL | 2024-10-21 |
| 969 | Large Language Models in Computer Science Education: A Systematic Literature Review Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: Large language models (LLMs) are becoming increasingly better at a wide range of Natural Language Processing tasks (NLP), such as text generation and understanding. Recently, … |
Nishat Raihan; Mohammed Latif Siddiq; Joanna C. S. Santos; Marcos Zampieri; | ArXiv | 2024-10-21 |
| 970 | Learning to Differentiate Pairwise-Argument Representations for Implicit Discourse Relation Recognition Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To enable encoders to produce clearly distinguishable representations, we propose a joint learning framework. |
ZHIPANG WANG et. al. | cikm | 2024-10-21 |
| 971 | Comparative Study of Multilingual Idioms and Similes in Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This study addresses the gap in the literature concerning the comparative performance of LLMs in interpreting different types of figurative language across multiple languages. |
PARIA KHOSHTAB et. al. | arxiv-cs.CL | 2024-10-21 |
| 972 | BART-based Hierarchical Attentional Network for Sentence Ordering Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce a novel BART-based Hierarchical Attentional Ordering Network (BHAONet), aiming to address the coherence modeling challenge within paragraphs, which stands as a cornerstone in comprehension, generation, and reasoning tasks. |
Yiping Yang; Baiyun Cui; Yingming Li; | cikm | 2024-10-21 |
| 973 | Adsorb-Agent: Autonomous Identification of Stable Adsorption Configurations Via Large Language Model Agent Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this study, we also evaluatedthe performance of different LLMs, including GPT-4o, GPT-4o-mini,Claude-3.7-Sonnet, and DeepSeek-Chat, as the reasoning engine for Adsorb-Agent,with GPT-4o showing the strongest overall performance. |
Janghoon Ock; Radheesh Sharma Meda; Tirtha Vinchurkar; Yayati Jadhav; Amir Barati Farimani; | arxiv-cs.CL | 2024-10-21 |
| 974 | Inferring Visualization Intent from Conversation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We consider a conversational approach to visualization, where users specify their needs at each step in natural language, with a visualization being returned in turn. |
Haotian Li; Nithin Chalapathi; Huamin Qu; Alvin Cheung; Aditya G. Parameswaran; | cikm | 2024-10-21 |
| 975 | Improving Neuron-level Interpretability with White-box Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In our study, we introduce a white-box transformer-like architecture named Coding RAte TransformEr (CRATE), explicitly engineered to capture sparse, low-dimensional structures within data distributions. |
Hao Bai; Yi Ma; | arxiv-cs.CL | 2024-10-21 |
| 976 | Does ChatGPT Have A Poetic Style? Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We find that the GPT models, especially GPT-4, can successfully produce poems in a range of both common and uncommon English-language forms in superficial yet noteworthy ways, such as by producing poems of appropriate lengths for sonnets (14 lines), villanelles (19 lines), and sestinas (39 lines). |
Melanie Walsh; Anna Preus; Elizabeth Gronski; | arxiv-cs.CL | 2024-10-20 |
| 977 | Exploring Social Desirability Response Bias in Large Language Models: Evidence from GPT-4 Simulations Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Large language models (LLMs) are employed to simulate human-like responses in social surveys, yet it remains unclear if they develop biases like social desirability response (SDR) bias. |
Sanguk Lee; Kai-Qi Yang; Tai-Quan Peng; Ruth Heo; Hui Liu; | arxiv-cs.AI | 2024-10-20 |
| 978 | BERTtime Stories: Investigating The Role of Synthetic Story Data in Language Pre-training Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We describe our contribution to the Strict and Strict-Small tracks of the 2nd iteration of the BabyLM Challenge. |
Nikitas Theodoropoulos; Giorgos Filandrianos; Vassilis Lyberatos; Maria Lymperaiou; Giorgos Stamou; | arxiv-cs.CL | 2024-10-20 |
| 979 | DTPPO: Dual-Transformer Encoder-based Proximal Policy Optimization for Multi-UAV Navigation in Unseen Complex Environments Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Existing multi-agent deep reinforcement learning (MADRL) methods for multi-UAV navigation face challenges in generalization, particularly when applied to unseen complex environments. To address these limitations, we propose a Dual-Transformer Encoder-based Proximal Policy Optimization (DTPPO) method. |
Anning Wei; Jintao Liang; Kaiyuan Lin; Ziyue Li; Rui Zhao; | arxiv-cs.MA | 2024-10-19 |
| 980 | Medical-GAT: Cancer Document Classification Leveraging Graph-Based Residual Network for Scenarios with Limited Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This scarcity of annotated data impedes the development of effective machine learning models for cancer document classification. To address this challenge, we present a curated dataset of 1,874 biomedical abstracts, categorized into thyroid cancer, colon cancer, lung cancer, and generic topics. |
Elias Hossain; Tasfia Nuzhat; Shamsul Masum; Shahram Rahimi; Noorbakhsh Amiri Golilarz; | arxiv-cs.AI | 2024-10-19 |
| 981 | Automated Genre-Aware Article Scoring and Feedback Using Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper focuses on the development of an advanced intelligent article scoring system that not only assesses the overall quality of written work but also offers detailed feature-based scoring tailored to various article genres. |
CHIHANG WANG et. al. | arxiv-cs.CL | 2024-10-18 |
| 982 | XPerT: Extended Persistence Transformer Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a novel transformer architecture called the \textit{Extended Persistence Transformer (xPerT)}, which is highly scalable than the compared to Persformer, an existing transformer for persistence diagrams. |
Sehun Kim; | arxiv-cs.LG | 2024-10-18 |
| 983 | Harmony: A Home Agent for Responsive Management and Action Optimization with A Locally Deployed Large Language Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In order to optimize the privacy and economy of data processing while maintaining the powerful functions of LLMs, we propose Harmony, a smart home assistant framework that uses a locally deployable small-scale LLM. |
Ziqi Yin; Mingxin Zhang; Daisuke Kawahara; | arxiv-cs.HC | 2024-10-18 |
| 984 | From Solitary Directives to Interactive Encouragement! LLM Secure Code Generation By Natural Language Prompting Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work introduces SecCode, a framework that leverages an innovative interactive encouragement prompting (EP) technique for secure code generation with \textit{only NL} prompts. |
SHIGANG LIU et. al. | arxiv-cs.CR | 2024-10-18 |
| 985 | Detecting AI-Generated Texts in Cross-Domains Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Existing tools to detect text generated by a large language model (LLM) have met with certain success, but their performance can drop when dealing with texts in new domains. To tackle this issue, we train a ranking classifier called RoBERTa-Ranker, a modified version of RoBERTa, as a baseline model using a dataset we constructed that includes a wider variety of texts written by humans and generated by various LLMs. |
You Zhou; Jie Wang; | arxiv-cs.CL | 2024-10-17 |
| 986 | Transformer-Based Approaches for Sensor-Based Human Activity Recognition: Opportunities and Challenges Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We observe that transformer-based solutions pose higher computational demands, consistently yield inferior performance, and experience significant performance degradation when quantized to accommodate resource-constrained devices. |
Clayton Souza Leite; Henry Mauranen; Aziza Zhanabatyrova; Yu Xiao; | arxiv-cs.LG | 2024-10-17 |
| 987 | Transfer Learning on Transformers for Building Energy Consumption Forecasting — A Comparative Study Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study investigates the application of Transfer Learning (TL) on Transformer architectures to enhance building energy consumption forecasting. |
Robert Spencer; Surangika Ranathunga; Mikael Boulic; Andries van Heerden; Teo Susnjak; | arxiv-cs.LG | 2024-10-17 |
| 988 | SBI-RAG: Enhancing Math Word Problem Solving for Students Through Schema-Based Instruction and Retrieval-Augmented Generation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Schema-based instruction (SBI) is an evidence-based strategy that helps students categorize problems based on their structure, improving problem-solving accuracy. Building on this, we propose a Schema-Based Instruction Retrieval-Augmented Generation (SBI-RAG) framework that incorporates a large language model (LLM). |
Prakhar Dixit; Tim Oates; | arxiv-cs.LG | 2024-10-17 |
| 989 | Judgment of Learning: A Human Ability Beyond Generative Artificial Intelligence 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 Ulakçı; | arxiv-cs.CL | 2024-10-17 |
| 990 | Linguistically Grounded Analysis of Language Models Using Shapley Head Values Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we investigate the processing of morphosyntactic phenomena, by leveraging a recently proposed method for probing language models via Shapley Head Values (SHVs). |
Marcell Fekete; Johannes Bjerva; | arxiv-cs.CL | 2024-10-17 |
| 991 | Measuring and Modifying The Readability of English Texts with GPT-4 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Then, in a pre-registered human experiment (N = 59), we ask whether Turbo can reliably make text easier or harder to read. We find evidence to support this hypothesis, though considerable variance in human judgments remains unexplained. |
Sean Trott; Pamela D. Rivière; | arxiv-cs.CL | 2024-10-17 |
| 992 | Context-Scaling Versus Task-Scaling in In-Context Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Transformers exhibit In-Context Learning (ICL), where these models solve new tasks by using examples in the prompt without additional training. |
Amirhesam Abedsoltan; Adityanarayanan Radhakrishnan; Jingfeng Wu; Mikhail Belkin; | arxiv-cs.LG | 2024-10-16 |
| 993 | Unifying Economic and Language Models for Enhanced Sentiment Analysis of The Oil Market Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, these LMs often have difficulty with domain-specific terminology, limiting their effectiveness in the crude oil sector. Addressing this gap, we introduce CrudeBERT, a fine-tuned LM specifically for the crude oil market. |
Himmet Kaplan; Ralf-Peter Mundani; Heiko Rölke; Albert Weichselbraun; Martin Tschudy; | arxiv-cs.IR | 2024-10-16 |
| 994 | Stabilize The Latent Space for Image Autoregressive Modeling: A Unified Perspective Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This finding contrasts sharply with the field of NLP, where the autoregressive model GPT has established a commanding presence. To address this discrepancy, we introduce a unified perspective on the relationship between latent space and generative models, emphasizing the stability of latent space in image generative modeling. |
YONGXIN ZHU et. al. | arxiv-cs.CV | 2024-10-16 |
| 995 | When Not to Answer: Evaluating Prompts on GPT Models for Effective Abstention in Unanswerable Math Word Problems Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we investigate whether GPTs can appropriately respond to unanswerable math word problems by applying prompts typically used in solvable mathematical scenarios. |
Asir Saadat; Tasmia Binte Sogir; Md Taukir Azam Chowdhury; Syem Aziz; | arxiv-cs.CL | 2024-10-16 |
| 996 | Reconstruction of Differentially Private Text Sanitization Via Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose two attacks (black-box and white-box) based on the accessibility to LLMs and show that LLMs could connect the pair of DP-sanitized text and the corresponding private training data of LLMs by giving sample text pairs as instructions (in the black-box attacks) or fine-tuning data (in the white-box attacks). |
SHUCHAO PANG et. al. | arxiv-cs.CR | 2024-10-16 |
| 997 | SELF-BART : A Transformer-based Molecular Representation Model Using SELFIES Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we develop an encoder-decoder model based on BART that is capable of leaning molecular representations and generate new molecules. |
INDRA PRIYADARSINI et. al. | arxiv-cs.CE | 2024-10-16 |
| 998 | Jigsaw Puzzles: Splitting Harmful Questions to Jailbreak Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose Jigsaw Puzzles (JSP), a straightforward yet effective multi-turn jailbreak strategy against the advanced LLMs. |
Hao Yang; Lizhen Qu; Ehsan Shareghi; Gholamreza Haffari; | arxiv-cs.CL | 2024-10-15 |
| 999 | Table-LLM-Specialist: Language Model Specialists for Tables Using Iterative Generator-Validator Fine-tuning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose Table-LLM-Specialist, or Table-Specialist for short, as a new self-trained fine-tuning paradigm specifically designed for table tasks. |
JUNJIE XING et. al. | arxiv-cs.CL | 2024-10-15 |
| 1000 | In-Context Learning for Long-Context Sentiment Analysis on Infrastructure Project Opinions Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Large language models (LLMs) have achieved impressive results across various tasks. |
Alireza Shamshiri; Kyeong Rok Ryu; June Young Park; | arxiv-cs.CL | 2024-10-15 |