{"total":123,"rows":[{"id":"2307.03109","title":"A Survey on Evaluation of Large Language Models","created":"2023-07-06","cited_by_count":1242,"area":null},{"id":"2308.10620","title":"Large Language Models for Software Engineering: A Systematic Literature Review","created":"2023-08-21","cited_by_count":399,"area":null},{"id":"2402.03927","title":"Leak, Cheat, Repeat: Data Contamination and Evaluation Malpractices in Closed-Source LLMs","created":"2024-02-06","cited_by_count":229,"area":null},{"id":"2307.10928","title":"FLASK: Fine-grained Language Model Evaluation based on Alignment Skill Sets","created":"2023-07-20","cited_by_count":201,"area":"alignment"},{"id":"2406.04127","title":"Are We Done with MMLU?","created":"2024-06-06","cited_by_count":194,"area":null},{"id":"2309.13788","title":"Can LLM-Generated Misinformation Be Detected?","created":"2023-09-25","cited_by_count":177,"area":null},{"id":"2402.01781","title":"When Benchmarks are Targets: Revealing the Sensitivity of Large Language Model Leaderboards","created":"2024-02-01","cited_by_count":137,"area":null},{"id":"2403.02901","title":"A Comprehensive Survey on Process-Oriented Automatic Text Summarization with Exploration of LLM-Based Methods","created":"2024-03-05","cited_by_count":102,"area":null},{"id":"2407.04069","title":"A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and Recommendations","created":"2024-07-04","cited_by_count":85,"area":null},{"id":"2404.10981","title":"A Survey on Retrieval-Augmented Text Generation for Large Language Models","created":"2024-04-17","cited_by_count":77,"area":"rag"},{"id":"2501.10970","title":"The Alternative Annotator Test for LLM-as-a-Judge: How to Statistically Justify Replacing Human Annotators with LLMs","created":"2025-01-19","cited_by_count":74,"area":null},{"id":"2308.12488","title":"GPTEval: A Survey on Assessments of ChatGPT and GPT-4","created":"2023-08-24","cited_by_count":73,"area":null},{"id":"2310.14542","title":"Evaluating Large Language Models on Controlled Generation Tasks","created":"2023-10-23","cited_by_count":73,"area":null},{"id":"2405.04760","title":"Large Language Models for Cyber Security: A Systematic Literature Review","created":"2024-05-08","cited_by_count":68,"area":null},{"id":"2402.19379","title":"Wisdom of the Silicon Crowd: LLM Ensemble Prediction Capabilities Rival Human Crowd Accuracy","created":"2024-02-29","cited_by_count":67,"area":null},{"id":"2311.18702","title":"CritiqueLLM: Towards an Informative Critique Generation Model for Evaluation of Large Language Model Generation","created":"2023-11-30","cited_by_count":66,"area":null},{"id":"2310.10035","title":"Empirical Study of Zero-Shot NER with ChatGPT","created":"2023-10-16","cited_by_count":60,"area":null},{"id":"2407.15390","title":"ALLaM: Large Language Models for Arabic and English","created":"2024-07-22","cited_by_count":55,"area":null},{"id":"2404.14779","title":"Med42 -- Evaluating Fine-Tuning Strategies for Medical LLMs: Full-Parameter vs. Parameter-Efficient Approaches","created":"2024-04-23","cited_by_count":52,"area":null},{"id":"2402.16775","title":"A Comprehensive Evaluation of Quantization Strategies for Large Language Models","created":"2024-02-26","cited_by_count":48,"area":null},{"id":"2311.09022","title":"Exploring the Potential of Large Language Models in Computational Argumentation","created":"2023-11-15","cited_by_count":42,"area":null},{"id":"2309.00754","title":"Efficient RLHF: Reducing the Memory Usage of PPO","created":"2023-09-01","cited_by_count":40,"area":"alignment"},{"id":"2312.12683","title":"Turning English-centric LLMs Into Polyglots: How Much Multilinguality Is Needed?","created":"2023-12-20","cited_by_count":39,"area":null},{"id":"2309.10952","title":"LMDX: Language Model-based Document Information Extraction and Localization","created":"2023-09-19","cited_by_count":37,"area":null},{"id":"2310.04270","title":"A Comprehensive Evaluation of Large Language Models on Benchmark Biomedical Text Processing Tasks","created":"2023-10-06","cited_by_count":36,"area":null},{"id":"2401.12491","title":"Assessing and Understanding Creativity in Large Language Models","created":"2024-01-23","cited_by_count":35,"area":null},{"id":"2310.19233","title":"Building Real-World Meeting Summarization Systems using Large Language Models: A Practical Perspective","created":"2023-10-30","cited_by_count":34,"area":null},{"id":"2402.00841","title":"Tiny Titans: Can Smaller Large Language Models Punch Above Their Weight in the Real World for Meeting Summarization?","created":"2024-02-01","cited_by_count":33,"area":null},{"id":"2309.07418","title":"A Fast Optimization View: Reformulating Single Layer Attention in LLM Based on Tensor and SVM Trick, and Solving It in Matrix Multiplication Time","created":"2023-09-14","cited_by_count":30,"area":null},{"id":"2404.02806","title":"The RealHumanEval: Evaluating Large Language Models' Abilities to Support Programmers","created":"2024-04-03","cited_by_count":30,"area":null},{"id":"2310.11053","title":"Denevil: Towards Deciphering and Navigating the Ethical Values of Large Language Models via Instruction Learning","created":"2023-10-17","cited_by_count":26,"area":null},{"id":"2402.00858","title":"Can Large Language Models Understand Context?","created":"2024-02-01","cited_by_count":26,"area":null},{"id":"2311.00681","title":"Are Large Language Models Reliable Judges? A Study on the Factuality Evaluation Capabilities of LLMs","created":"2023-11-01","cited_by_count":24,"area":null},{"id":"2309.13173","title":"BenLLMEval: A Comprehensive Evaluation into the Potentials and Pitfalls of Large Language Models on Bengali NLP","created":"2023-09-22","cited_by_count":23,"area":null},{"id":"2306.04504","title":"Evaluation of ChatGPT on Biomedical Tasks: A Zero-Shot Comparison with Fine-Tuned Generative Transformers","created":"2023-06-07","cited_by_count":22,"area":null},{"id":"2402.12011","title":"A Systematic Comparison of Contextualized Word Embeddings for Lexical Semantic Change","created":"2024-02-19","cited_by_count":21,"area":null},{"id":"2410.20245","title":"Improving Model Evaluation using SMART Filtering of Benchmark Datasets","created":"2024-10-26","cited_by_count":21,"area":null},{"id":"2403.00784","title":"Utilizing BERT for Information Retrieval: Survey, Applications, Resources, and Challenges","created":"2024-02-18","cited_by_count":20,"area":null},{"id":"2510.19032","title":"When Can We Trust LLMs in Mental Health? Large-Scale Benchmarks for Reliable LLM Evaluation","created":"2025-10-21","cited_by_count":19,"area":null},{"id":"2406.05063","title":"Are Large Language Models More Empathetic than Humans?","created":"2024-06-07","cited_by_count":18,"area":null},{"id":"2503.02911","title":"Text2Scenario: Text-Driven Scenario Generation for Autonomous Driving Test","created":"2025-03-04","cited_by_count":18,"area":"driving"},{"id":"2309.05454","title":"Flesch or Fumble? Evaluating Readability Standard Alignment of Instruction-Tuned Language Models","created":"2023-09-11","cited_by_count":17,"area":null},{"id":"2308.03051","title":"TARJAMAT: Evaluation of Bard and ChatGPT on Machine Translation of Ten Arabic Varieties","created":"2023-08-06","cited_by_count":16,"area":null},{"id":"2406.16655","title":"Large Language Models Are Cross-Lingual Knowledge-Free Reasoners","created":"2024-06-24","cited_by_count":16,"area":"lr"},{"id":"2404.01667","title":"METAL: Towards Multilingual Meta-Evaluation","created":"2024-04-02","cited_by_count":15,"area":null},{"id":"2309.12485","title":"Studying and improving reasoning in humans and machines","created":"2023-09-21","cited_by_count":14,"area":"lr"},{"id":"2402.14261","title":"Copilot Evaluation Harness: Evaluating LLM-Guided Software Programming","created":"2024-02-22","cited_by_count":13,"area":null},{"id":"2408.17026","title":"From Text to Emotion: Unveiling the Emotion Annotation Capabilities of LLMs","created":"2024-08-30","cited_by_count":13,"area":null},{"id":"2506.00777","title":"Improving Automatic Evaluation of Large Language Models (LLMs) in Biomedical Relation Extraction via LLMs-as-the-Judge","created":"2025-06-01","cited_by_count":13,"area":null},{"id":"2309.07938","title":"An Assessment of ChatGPT on Log Data","created":"2023-09-14","cited_by_count":12,"area":null},{"id":"2406.10291","title":"ResearchArena: Benchmarking Large Language Models' Ability to Collect and Organize Information as Research Agents","created":"2024-06-13","cited_by_count":12,"area":"agents"},{"id":"2404.10947","title":"Residual Connections Harm Generative Representation Learning","created":"2024-04-16","cited_by_count":11,"area":"diffusion"},{"id":"2309.16573","title":"Language Models as a Service: Overview of a New Paradigm and its Challenges","created":"2023-09-28","cited_by_count":10,"area":null},{"id":"2309.08210","title":"Investigating Answerability of LLMs for Long-Form Question Answering","created":"2023-09-15","cited_by_count":9,"area":null},{"id":"2310.13615","title":"Three Questions Concerning the Use of Large Language Models to Facilitate Mathematics Learning","created":"2023-10-20","cited_by_count":9,"area":null},{"id":"2403.00067","title":"Query-OPT: Optimizing Inference of Large Language Models via Multi-Query Instructions in Meeting Summarization","created":"2024-02-29","cited_by_count":9,"area":null},{"id":"2404.10155","title":"The Fault in our Stars: Quality Assessment of Code Generation Benchmarks","created":"2024-04-15","cited_by_count":9,"area":null},{"id":"2505.13535","title":"Information Extraction from Visually Rich Documents using LLM-based Organization of Documents into Independent Textual Segments","created":"2025-05-18","cited_by_count":9,"area":null},{"id":"2312.04578","title":"Towards a Psychological Generalist AI: A Survey of Current Applications of Large Language Models and Future Prospects","created":"2023-12-01","cited_by_count":8,"area":null},{"id":"2401.14040","title":"(Chat)GPT v BERT: Dawn of Justice for Semantic Change Detection","created":"2024-01-25","cited_by_count":8,"area":null},{"id":"2402.14860","title":"Ranking Large Language Models without Ground Truth","created":"2024-02-21","cited_by_count":8,"area":null},{"id":"2403.05572","title":"Is ChatGPT More Empathetic than Humans?","created":"2024-02-22","cited_by_count":8,"area":null},{"id":"2408.12214","title":"Bridging Large Language Models and Optimization: A Unified Framework for Text-attributed Combinatorial Optimization","created":"2024-08-22","cited_by_count":8,"area":null},{"id":"2506.07626","title":"Intent Matters: Enhancing AI Tutoring with Fine-Grained Pedagogical Intent Annotation","created":"2025-06-09","cited_by_count":8,"area":null},{"id":"2403.14965","title":"Comprehensive Evaluation and Insights into the Use of Large Language Models in the Automation of Behavior-Driven Development Acceptance Test Formulation","created":"2024-03-22","cited_by_count":7,"area":null},{"id":"2506.00309","title":"Evaluation of LLMs for mathematical problem solving","created":"2025-05-30","cited_by_count":7,"area":null},{"id":"2307.08152","title":"The Potential and Pitfalls of using a Large Language Model such as ChatGPT or GPT-4 as a Clinical Assistant","created":"2023-07-16","cited_by_count":6,"area":null},{"id":"2502.18702","title":"A Cooperative Multi-Agent Framework for Zero-Shot Named Entity Recognition","created":"2025-02-25","cited_by_count":6,"area":"agents"},{"id":"2601.13260","title":"Stop Taking Tokenizers for Granted: They Are Core Design Decisions in Large Language Models","created":"2026-01-19","cited_by_count":6,"area":null},{"id":"2402.03130","title":"User Centric Evaluation of Code Generation Tools","created":"2024-02-05","cited_by_count":5,"area":null},{"id":"2402.10767","title":"Inference to the Best Explanation in Large Language Models","created":"2024-02-16","cited_by_count":5,"area":null},{"id":"2403.05652","title":"\"What is Different Between These Datasets?\" A Framework for Explaining Data Distribution Shifts","created":"2024-03-08","cited_by_count":5,"area":null},{"id":"2406.10786","title":"Evaluating LLMs with Multiple Problems at once","created":"2024-06-16","cited_by_count":5,"area":null},{"id":"2407.01091","title":"M2QA: Multi-domain Multilingual Question Answering","created":"2024-07-01","cited_by_count":5,"area":null},{"id":"2504.12562","title":"ZeroSumEval: Scaling LLM Evaluation with Inter-Model Competition","created":"2025-04-17","cited_by_count":5,"area":null},{"id":"2509.12248","title":"Humor in Pixels: Benchmarking Large Multimodal Models Understanding of Online Comics","created":"2025-09-12","cited_by_count":5,"area":"mllm"},{"id":"2510.08149","title":"AI Knowledge Assist: An Automated Approach for the Creation of Knowledge Bases for Conversational AI Agents","created":"2025-10-09","cited_by_count":5,"area":"rag"},{"id":"2605.15104","title":"From Text to Voice: A Reproducible and Verifiable Framework for Evaluating Tool Calling LLM Agents","created":"2026-05-14","cited_by_count":5,"area":"agents"},{"id":"2310.16810","title":"Can GPT models Follow Human Summarization Guidelines? A Study for Targeted Communication Goals","created":"2023-10-25","cited_by_count":4,"area":null},{"id":"2311.05020","title":"First Tragedy, then Parse: History Repeats Itself in the New Era of Large Language Models","created":"2023-11-08","cited_by_count":4,"area":null},{"id":"2410.02741","title":"Salient Information Prompting to Steer Content in Prompt-based Abstractive Summarization","created":"2024-10-03","cited_by_count":4,"area":null},{"id":"2602.01472","title":"ConPress: Learning Efficient Reasoning from Multi-Question Contextual Pressure","created":"2026-02-01","cited_by_count":4,"area":"lr"},{"id":"2608.01021","title":"Can Humans Dream of Electric Sheep? Human-Written Samples for Fine-Grained Vision-and-Language Hallucination Benchmarking","created":"2026-08-02","cited_by_count":4,"area":null},{"id":"2310.14557","title":"The Skipped Beat: A Study of Sociopragmatic Understanding in LLMs for 64 Languages","created":"2023-10-23","cited_by_count":3,"area":null},{"id":"2311.13053","title":"Beyond Text: Unveiling Multimodal Proficiency of Large Language Models with MultiAPI Benchmark","created":"2023-11-21","cited_by_count":3,"area":null},{"id":"2401.00761","title":"Identifying the Achilles' Heel: An Iterative Method for Dynamically Uncovering Factual Errors in Large Language Models","created":"2024-01-01","cited_by_count":3,"area":null},{"id":"2402.01841","title":"COMET: Generating Commit Messages using Delta Graph Context Representation","created":"2024-02-02","cited_by_count":3,"area":null},{"id":"2407.21072","title":"Beyond Metrics: A Critical Analysis of the Variability in Large Language Model Evaluation Frameworks","created":"2024-07-29","cited_by_count":3,"area":null},{"id":"2503.16456","title":"Position: Beyond Assistance -- Reimagining LLMs as Ethical and Adaptive Co-Creators in Mental Health Care","created":"2025-02-21","cited_by_count":3,"area":null},{"id":"2401.10472","title":"Named Entity Recognition Under Domain Shift via Metric Learning for Life Sciences","created":"2024-01-19","cited_by_count":2,"area":null},{"id":"2402.11203","title":"Exploring ChatGPT for Next-generation Information Retrieval: Opportunities and Challenges","created":"2024-02-17","cited_by_count":2,"area":null},{"id":"2403.15886","title":"Leveraging Zero-Shot Prompting for Efficient Language Model Distillation","created":"2024-03-23","cited_by_count":2,"area":"distill"},{"id":"2406.14171","title":"Ranking LLMs by compression","created":"2024-06-20","cited_by_count":2,"area":null},{"id":"2406.15809","title":"LaMSUM: Amplifying Voices Against Harassment through LLM Guided Extractive Summarization of User Incident Reports","created":"2024-06-22","cited_by_count":2,"area":null},{"id":"2408.08907","title":"What should I wear to a party in a Greek taverna? Evaluation for Conversational Agents in the Fashion Domain","created":"2024-08-13","cited_by_count":2,"area":"agents"},{"id":"2505.04666","title":"Fine-Tuning Large Language Models and Evaluating Retrieval Methods for Improved Question Answering on Building Codes","created":"2025-05-07","cited_by_count":2,"area":"rag"},{"id":"2505.23996","title":"Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs","created":"2025-05-29","cited_by_count":2,"area":null},{"id":"2507.14045","title":"Evaluating the Effectiveness of Cost-Efficient Large Language Models in Benchmark Biomedical Tasks","created":"2025-07-18","cited_by_count":2,"area":null},{"id":"2510.05858","title":"DACP: Domain-Adaptive Continual Pre-Training of Large Language Models for Phone Conversation Summarization","created":"2025-10-07","cited_by_count":2,"area":null},{"id":"2601.04582","title":"Aligning Text, Code, and Vision: A Multi-Objective Reinforcement Learning Framework for Text-to-Visualization","created":"2026-01-08","cited_by_count":2,"area":null}],"next_cursor":"100"}