{"total":214,"rows":[{"id":"2411.16594","title":"From Generation to Judgment: Opportunities and Challenges of LLM-as-a-judge","created":"2024-11-25","cited_by_count":494,"area":null},{"id":"2412.05579","title":"LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods","created":"2024-12-07","cited_by_count":465,"area":null},{"id":"2505.08775","title":"HealthBench: Evaluating Large Language Models Towards Improved Human Health","created":"2025-05-13","cited_by_count":429,"area":null},{"id":"2502.01534","title":"Preference Leakage: A Contamination Problem in LLM-as-a-judge","created":"2025-02-03","cited_by_count":125,"area":null},{"id":"2502.11221","title":"PlanGenLLMs: A Modern Survey of LLM Planning Capabilities","created":"2025-02-16","cited_by_count":83,"area":null},{"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":"2503.05061","title":"No Free Labels: Limitations of LLM-as-a-Judge Without Human Grounding","created":"2025-03-07","cited_by_count":54,"area":null},{"id":"2501.03200","title":"The FACTS Grounding Leaderboard: Benchmarking LLMs' Ability to Ground Responses to Long-Form Input","created":"2025-01-06","cited_by_count":52,"area":null},{"id":"2506.22316","title":"Evaluating Scoring Bias in LLM-as-a-Judge","created":"2025-06-27","cited_by_count":43,"area":null},{"id":"2508.18076","title":"Neither Valid nor Reliable? Investigating the Use of LLMs as Judges","created":"2025-08-25","cited_by_count":39,"area":null},{"id":"2508.06709","title":"Play Favorites: A Statistical Method to Measure Self-Bias in LLM-as-a-Judge","created":"2025-08-08","cited_by_count":36,"area":null},{"id":"2410.15393","title":"CalibraEval: Calibrating Prediction Distribution to Mitigate Selection Bias in LLMs-as-Judges","created":"2024-10-20","cited_by_count":34,"area":null},{"id":"2410.15413","title":"A Comprehensive Evaluation of Cognitive Biases in LLMs","created":"2024-10-20","cited_by_count":34,"area":null},{"id":"2503.17489","title":"Judge Anything: MLLM as a Judge Across Any Modality","created":"2025-03-21","cited_by_count":34,"area":null},{"id":"2502.12084","title":"VLM2-Bench: A Closer Look at How Well VLMs Implicitly Link Explicit Matching Visual Cues","created":"2025-02-17","cited_by_count":33,"area":null},{"id":"2505.12201","title":"How Reliable is Multilingual LLM-as-a-Judge?","created":"2025-05-18","cited_by_count":30,"area":null},{"id":"2412.09569","title":"JuStRank: Benchmarking LLM Judges for System Ranking","created":"2024-12-12","cited_by_count":29,"area":null},{"id":"2504.17768","title":"The Sparse Frontier: Sparse Attention Trade-offs in Transformer LLMs","created":"2025-04-24","cited_by_count":29,"area":null},{"id":"2410.23426","title":"Social Science Meets LLMs: How Reliable Are Large Language Models in Social Simulations?","created":"2024-10-30","cited_by_count":26,"area":null},{"id":"2605.29800","title":"Nine Judges, Two Effective Votes: Correlated Errors Undermine LLM Evaluation Panels","created":"2026-05-28","cited_by_count":26,"area":null},{"id":"2601.20913","title":"Noisy but Valid: Robust Statistical Evaluation of LLMs with Imperfect Judges","created":"2026-01-28","cited_by_count":24,"area":null},{"id":"2506.10150","title":"When Large Language Models are Reliable for Judging Empathic Communication","created":"2025-06-11","cited_by_count":21,"area":null},{"id":"2506.13639","title":"An Empirical Study of LLM-as-a-Judge: How Design Choices Impact Evaluation Reliability","created":"2025-06-16","cited_by_count":19,"area":null},{"id":"2509.17995","title":"Variation in Verification: Understanding Verification Dynamics in Large Language Models","created":"2025-09-22","cited_by_count":19,"area":null},{"id":"2511.16931","title":"OmniScientist: Toward a Co-evolving Ecosystem of Human and AI Scientists","created":"2025-11-21","cited_by_count":18,"area":null},{"id":"2503.05085","title":"S2S-Arena: Evaluating Paralinguistic Instruction Following in Speech-to-Speech Models","created":"2025-03-07","cited_by_count":16,"area":null},{"id":"2505.24778","title":"Revisiting Epistemic Markers in Confidence Estimation: Can Markers Accurately Reflect Large Language Models' Uncertainty?","created":"2025-05-30","cited_by_count":16,"area":null},{"id":"2602.00521","title":"Diagnosing the Reliability of LLM-as-a-Judge via Item Response Theory","created":"2026-01-31","cited_by_count":16,"area":null},{"id":"2502.03629","title":"REALEDIT: Reddit Edits As a Large-scale Empirical Dataset for Image Transformations","created":"2025-02-05","cited_by_count":15,"area":null},{"id":"2603.11510","title":"Tiny Aya: Bridging Scale and Multilingual Depth","created":"2026-03-12","cited_by_count":15,"area":null},{"id":"2511.03108","title":"miniF2F-Lean Revisited: Reviewing Limitations and Charting a Path Forward","created":"2025-11-05","cited_by_count":14,"area":null},{"id":"2602.09383","title":"BiasScope: Towards Automated Detection of Bias in LLM-as-a-Judge Evaluation","created":"2026-02-10","cited_by_count":14,"area":null},{"id":"2504.07069","title":"HalluciNot: Hallucination Detection Through Context and Common Knowledge Verification","created":"2025-04-09","cited_by_count":13,"area":null},{"id":"2603.00039","title":"CARE: Confounder-Aware Aggregation for Reliable LLM Evaluation","created":"2026-02-09","cited_by_count":13,"area":null},{"id":"2505.18596","title":"Debate-to-Detect: Reformulating Misinformation Detection as a Real-World Debate with Large Language Models","created":"2025-05-24","cited_by_count":12,"area":null},{"id":"2502.01349","title":"Bias Beware: The Impact of Cognitive Biases on LLM-Driven Product Recommendations","created":"2025-02-03","cited_by_count":11,"area":null},{"id":"2507.22879","title":"RecGPT Technical Report","created":"2025-07-30","cited_by_count":11,"area":null},{"id":"2510.18560","title":"WebDevJudge: Evaluating (M)LLMs as Critiques for Web Development Quality","created":"2025-10-21","cited_by_count":11,"area":null},{"id":"2605.18661","title":"AI for Auto-Research: Roadmap & User Guide","created":"2026-05-18","cited_by_count":11,"area":null},{"id":"2502.01609","title":"Adaptive Distraction: Probing LLM Contextual Robustness with Automated Tree Search","created":"2025-02-03","cited_by_count":10,"area":null},{"id":"2502.03688","title":"A Comparison of DeepSeek and Other LLMs","created":"2025-02-06","cited_by_count":10,"area":null},{"id":"2502.17787","title":"AIR: Complex Instruction Generation via Automatic Iterative Refinement","created":"2025-02-25","cited_by_count":10,"area":null},{"id":"2511.18491","title":"MindEval: Benchmarking Language Models on Multi-turn Mental Health Support","created":"2025-11-23","cited_by_count":10,"area":null},{"id":"2601.05752","title":"AutoMonitor-Bench: Evaluating the Reliability of LLM-Based Misbehavior Monitor","created":"2026-01-09","cited_by_count":10,"area":null},{"id":"2503.04804","title":"What do Large Language Models Say About Animals? Investigating Risks of Animal Harm in Generated Text","created":"2025-03-03","cited_by_count":9,"area":null},{"id":"2602.12966","title":"ProbeLLM: Automating Principled Diagnosis of LLM Failures","created":"2026-02-13","cited_by_count":9,"area":null},{"id":"2509.22957","title":"Doubly-Robust LLM-as-a-Judge: Externally Valid Estimation with Imperfect Personas","created":"2025-09-26","cited_by_count":8,"area":null},{"id":"2509.25154","title":"Who's Your Judge? On the Detectability of LLM-Generated Judgments","created":"2025-09-29","cited_by_count":8,"area":null},{"id":"2510.15232","title":"FinTrust: A Comprehensive Benchmark of Trustworthiness Evaluation in Finance Domain","created":"2025-10-17","cited_by_count":8,"area":null},{"id":"2601.06884","title":"Paraphrasing Adversarial Attack on LLM-as-a-Reviewer","created":"2026-01-11","cited_by_count":8,"area":null},{"id":"2606.01637","title":"Easier to Mislead Than to Correct: Harmful and Beneficial Revision in LLM Conformity","created":"2026-06-01","cited_by_count":8,"area":null},{"id":"2503.17684","title":"Can LLMs Automate Fact-Checking Article Writing?","created":"2025-03-22","cited_by_count":7,"area":null},{"id":"2508.12792","title":"Bridging Human and LLM Judgments: Understanding and Narrowing the Gap","created":"2025-08-18","cited_by_count":7,"area":null},{"id":"2511.12920","title":"Auditing Google's AI Overviews and Featured Snippets: A Case Study on Baby Care and Pregnancy","created":"2025-11-17","cited_by_count":7,"area":null},{"id":"2606.07612","title":"Position: Anthropomorphic Misalignment Research Needs Stronger Evidence","created":"2026-05-29","cited_by_count":7,"area":null},{"id":"2502.18331","title":"BottleHumor: Self-Informed Humor Explanation using the Information Bottleneck Principle","created":"2025-02-22","cited_by_count":6,"area":null},{"id":"2503.08542","title":"CLEV: LLM-Based Evaluation Through Lightweight Efficient Voting for Free-Form Question-Answering","created":"2025-03-11","cited_by_count":6,"area":null},{"id":"2506.10403","title":"Time To Impeach LLM-as-a-Judge: Programs are the Future of Evaluation","created":"2025-06-12","cited_by_count":6,"area":null},{"id":"2508.08777","title":"Evaluating Podcast Recommendations with Profile-Aware LLM-as-a-Judge","created":"2025-08-12","cited_by_count":6,"area":null},{"id":"2510.05154","title":"Can AI Truly Represent Your Voice in Deliberations? A Comprehensive Study of Large-Scale Opinion Aggregation with LLMs","created":"2025-10-02","cited_by_count":6,"area":null},{"id":"2510.12462","title":"Evaluating and Mitigating LLM-as-a-judge Bias in Communication Systems","created":"2025-10-14","cited_by_count":6,"area":null},{"id":"2602.02219","title":"Am I More Pointwise or Pairwise? Revealing Position Bias in Rubric-Based LLM-as-a-Judge","created":"2026-02-02","cited_by_count":6,"area":null},{"id":"2503.16423","title":"GAEA: A Geolocation Aware Conversational Assistant","created":"2025-03-20","cited_by_count":5,"area":null},{"id":"2505.17691","title":"ELSPR: Evaluator LLM Training Data Self-Purification on Non-Transitive Preferences via Tournament Graph Reconstruction","created":"2025-05-23","cited_by_count":5,"area":null},{"id":"2506.00178","title":"Tournament of Prompts: Evolving LLM Instructions Through Structured Debates and Elo Ratings","created":"2025-05-30","cited_by_count":5,"area":null},{"id":"2506.12263","title":"A Survey of Foundation Models for IoT: Taxonomy and Criteria-Based Analysis","created":"2025-06-13","cited_by_count":5,"area":null},{"id":"2601.22548","title":"Are LLM Evaluators Really Narcissists? Sanity Checking Self-Preference Evaluations","created":"2026-01-30","cited_by_count":5,"area":null},{"id":"2603.29403","title":"Security in LLM-as-a-Judge: A Comprehensive SoK","created":"2026-03-31","cited_by_count":5,"area":null},{"id":"2608.02046","title":"CompanionBench: A Theory-Anchored, Real-World-Grounded Benchmark for AI Emotional Companionship","created":"2026-08-03","cited_by_count":5,"area":null},{"id":"2504.04141","title":"Self-Adaptive Cognitive Debiasing for Large Language Models in Decision-Making","created":"2025-04-05","cited_by_count":4,"area":null},{"id":"2505.00065","title":"ConSens: Assessing context grounding in open-book question answering","created":"2025-04-30","cited_by_count":4,"area":null},{"id":"2507.17717","title":"From Feedback to Checklists: Grounded Evaluation of AI-Generated Clinical Notes","created":"2025-07-23","cited_by_count":4,"area":null},{"id":"2509.05818","title":"Chatbot To Help Patients Understand Their Health","created":"2025-09-06","cited_by_count":4,"area":null},{"id":"2510.15217","title":"Reflections from Research Roundtables at the Conference on Health, Inference, and Learning (CHIL) 2025","created":"2025-10-17","cited_by_count":4,"area":null},{"id":"2511.01014","title":"IF-CRITIC: Towards a Fine-Grained LLM Critic for Instruction-Following Evaluation","created":"2025-11-02","cited_by_count":4,"area":null},{"id":"2601.08901","title":"Navigating Ideation Space: Decomposed Conceptual Representations for Positioning Scientific Ideas","created":"2026-01-13","cited_by_count":4,"area":null},{"id":"2602.02589","title":"PeerRank: Autonomous LLM Evaluation Through Web-Grounded, Bias-Controlled Peer Review","created":"2026-02-01","cited_by_count":4,"area":null},{"id":"2604.07650","title":"A Statistical Framework for Auditing Behavioral Dependence and Induced Bias in LLM Judges","created":"2026-04-08","cited_by_count":4,"area":null},{"id":"2605.10267","title":"IndustryBench: Probing the Industrial Knowledge Boundaries of LLMs","created":"2026-05-11","cited_by_count":4,"area":null},{"id":"2605.26156","title":"Turning Bias into Bugs: Bandit-Guided Style Manipulation Attacks on LLM Judges","created":"2026-05-24","cited_by_count":4,"area":null},{"id":"2607.12885","title":"LLM Judges Can Be Too Generous When There Is No Reference Answer","created":"2026-07-14","cited_by_count":4,"area":null},{"id":"2609.30243","title":"JevOut: Natural Context Can Flip Decision Models","created":"2026-09-24","cited_by_count":4,"area":null},{"id":"2502.06655","title":"Unbiased Evaluation of Large Language Models from a Causal Perspective","created":"2025-02-10","cited_by_count":3,"area":null},{"id":"2505.17149","title":"Large Language Models for Predictive Analysis: How Far Are They?","created":"2025-05-22","cited_by_count":3,"area":null},{"id":"2506.17294","title":"From Multimodal Perception to Strategic Reasoning: A Survey on AI-Generated Game Commentary","created":"2025-06-17","cited_by_count":3,"area":null},{"id":"2507.08335","title":"MK2 at PBIG Competition: A Prompt Generation Solution","created":"2025-07-11","cited_by_count":3,"area":null},{"id":"2510.18196","title":"Contrastive Decoding Mitigates Score Range Bias in LLM-as-a-Judge","created":"2025-10-21","cited_by_count":3,"area":null},{"id":"2510.20860","title":"Data-Centric Lessons To Improve Speech-Language Pretraining","created":"2025-10-22","cited_by_count":3,"area":null},{"id":"2511.00092","title":"QuantumBench: A Benchmark for Quantum Problem Solving","created":"2025-10-30","cited_by_count":3,"area":null},{"id":"2511.01807","title":"Plan-and-Write: Structure-Guided Length Control for LLMs without Model Retraining","created":"2025-11-03","cited_by_count":3,"area":null},{"id":"2511.09785","title":"AI Annotation Orchestration: Evaluating LLM verifiers to Improve the Quality of LLM Annotations in Learning Analytics","created":"2025-11-12","cited_by_count":3,"area":null},{"id":"2601.13649","title":"Fairness or Fluency? An Investigation into Language Bias of Pairwise LLM-as-a-Judge","created":"2026-01-20","cited_by_count":3,"area":null},{"id":"2601.14698","title":"ClaimDB: A Fact Verification Benchmark over Large Structured Data","created":"2026-01-21","cited_by_count":3,"area":null},{"id":"2601.17312","title":"Meta-Judging with Large Language Models: Concepts, Methods, and Challenges","created":"2026-01-24","cited_by_count":3,"area":null},{"id":"2602.01532","title":"PRISM: Festina Lente Proactivity -- Risk-Sensitive, Uncertainty-Aware Deliberation for Proactive Agents","created":"2026-02-02","cited_by_count":3,"area":null},{"id":"2603.26516","title":"ALBA: A European Portuguese Benchmark for Evaluating Language and Linguistic Dimensions in Generative LLMs","created":"2026-03-27","cited_by_count":3,"area":null},{"id":"2603.28304","title":"The Necessity of Setting Temperature in LLM-as-a-Judge","created":"2026-03-30","cited_by_count":3,"area":null},{"id":"2604.02359","title":"Using LLM-as-a-Judge/Jury to Advance Scalable, Clinically-Validated Safety Evaluations of Model Responses to Users Demonstrating Psychosis","created":"2026-03-20","cited_by_count":3,"area":null},{"id":"2604.05593","title":"Label Effects: Shared Heuristic Reliance in Trust Assessment by Humans and LLM-as-a-Judge","created":"2026-04-07","cited_by_count":3,"area":null},{"id":"2605.10379","title":"Not All Proofs Are Equal: Evaluating LLM Proof Quality Beyond Correctness","created":"2026-05-11","cited_by_count":3,"area":null}],"next_cursor":"100"}