{"total":53,"rows":[{"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":"2510.11408","title":"Valid Survey Simulations with Limited Human Data: The Roles of Prompting, Fine-Tuning, and Rectification","created":"2025-10-13","cited_by_count":18,"area":null},{"id":"2509.04484","title":"The Good, the Bad and the Constructive: Automatically Measuring Peer Review's Utility for Authors","created":"2025-08-31","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":"2602.02464","title":"From Directions to Regions: Decomposing Activations in Language Models via Local Geometry","created":"2026-02-02","cited_by_count":12,"area":null},{"id":"2505.22586","title":"Precise In-Parameter Concept Erasure in Large Language Models","created":"2025-05-28","cited_by_count":11,"area":null},{"id":"2601.19532","title":"Benchmarks Saturate When The Model Gets Smarter Than The Judge","created":"2026-01-27","cited_by_count":11,"area":null},{"id":"2609.24574","title":"Evaluating Decision Models for Text Annotation in Computational Social Science","created":"2026-09-21","cited_by_count":11,"area":null},{"id":"2604.11581","title":"Hidden Measurement Error in LLM Pipelines Distorts Annotation, Evaluation, and Benchmarking","created":"2026-04-13","cited_by_count":10,"area":null},{"id":"2507.17015","title":"Can External Validation Tools Improve Annotation Quality for LLM-as-a-Judge?","created":"2025-07-22","cited_by_count":9,"area":null},{"id":"2507.15339","title":"LionGuard 2: Building Lightweight, Data-Efficient & Localised Multilingual Content Moderators","created":"2025-07-21","cited_by_count":7,"area":null},{"id":"2510.01474","title":"AIReg-Bench: Benchmarking Language Models That Assess AI Regulation Compliance","created":"2025-10-01","cited_by_count":6,"area":null},{"id":"2504.12589","title":"Efficient MAP Estimation of LLM Judgment Performance with Prior Transfer","created":"2025-04-17","cited_by_count":4,"area":null},{"id":"2505.20209","title":"Improving the OOD Performance of Closed-Source LLMs on NLI Through Strategic Data Selection","created":"2025-05-26","cited_by_count":4,"area":null},{"id":"2510.08111","title":"Evaluating LLM-Generated Legal Explanations for Regulatory Compliance in Social Media Influencer Marketing","created":"2025-10-09","cited_by_count":4,"area":null},{"id":"2507.00828","title":"ProxAnn: Use-Oriented Evaluations of Topic Models and Document Clustering","created":"2025-07-01","cited_by_count":3,"area":null},{"id":"2605.02122","title":"STABLEVAL: Disagreement-Aware and Stable Evaluation of AI Systems","created":"2026-05-04","cited_by_count":3,"area":null},{"id":"2605.06283","title":"Quantifying the Statistical Effect of Rubric Modifications on Human-Autorater Agreement","created":"2026-05-07","cited_by_count":3,"area":null},{"id":"2606.03043","title":"The Geometry of LLM-as-Judge: Why Inter-LLM Consensus Is Not Human Alignment","created":"2026-06-02","cited_by_count":3,"area":null},{"id":"2505.13418","title":"Dementia Through Different Eyes: Explainable Modeling of Human and LLM Perceptions for Early Awareness","created":"2025-05-19","cited_by_count":2,"area":null},{"id":"2602.11318","title":"The Consensus Trap: Dissecting Subjectivity and the \"Ground Truth\" Illusion in Data Annotation","created":"2026-02-11","cited_by_count":2,"area":null},{"id":"2606.11018","title":"Measuring Human Value Expression in Social Media Texts: Calibrated LLM Annotation and Encoder Transfer","created":"2026-06-09","cited_by_count":2,"area":null},{"id":"2606.11105","title":"PhantomBench: Benchmarking the Non-existential Threat of Language Models","created":"2026-06-09","cited_by_count":2,"area":null},{"id":"2510.25577","title":"Lost in Phonation: Voice Quality Variation as an Evaluation Dimension for Speech Foundation Models","created":"2025-10-29","cited_by_count":1,"area":null},{"id":"2601.06106","title":"Judge Model for Large-scale Multimodality Benchmarks","created":"2026-01-03","cited_by_count":1,"area":null},{"id":"2603.03322","title":"Can Large Language Models Derive New Knowledge? A Dynamic Benchmark for Biological Knowledge Discovery","created":"2026-02-10","cited_by_count":1,"area":null},{"id":"2604.15873","title":"How Hypocritical Is Your LLM judge? Listener-Speaker Asymmetries in the Pragmatic Competence of Large Language Models","created":"2026-04-17","cited_by_count":1,"area":null},{"id":"2605.16023","title":"Judge Circuits Explain Format-Induced Inconsistency in LLM-as-a-Judge","created":"2026-05-15","cited_by_count":1,"area":null},{"id":"2608.06539","title":"Don't `Well, Actually' Me Unless You Know What You're Talking About: Weak Presupposition Verification Degrades General QA Performance","created":"2026-08-06","cited_by_count":1,"area":null},{"id":"2608.27463","title":"Rating the Raters: Rasch Measurement Theory for LLM Evaluation","created":"2026-07-14","cited_by_count":1,"area":null},{"id":"2609.25447","title":"Conduct Under Pressure: What Sixty Language Models Do When a User Pushes","created":"2026-09-21","cited_by_count":1,"area":null},{"id":"2502.00903","title":"Embracing Dialectic Intersubjectivity: Coordination of Different Perspectives in Content Analysis with LLM Persona Simulation","created":"2025-02-02","cited_by_count":0,"area":null},{"id":"2504.10768","title":"The Art of Audience Engagement: LLM-Based Thin-Slicing of Scientific Talks","created":"2025-04-15","cited_by_count":0,"area":null},{"id":"2505.19402","title":"Recalibrating the Compass: Integrating Large Language Models into Classical Research Methods","created":"2025-05-26","cited_by_count":0,"area":null},{"id":"2507.05385","title":"EduCoder: An Open-Source Annotation System for Education Transcript Data","created":"2025-07-07","cited_by_count":0,"area":null},{"id":"2511.11597","title":"CLINB: A Climate Intelligence Benchmark for Foundational Models","created":"2025-10-29","cited_by_count":0,"area":null},{"id":"2512.01958","title":"Learned-Rule-Augmented Large Language Model Evaluators","created":"2025-12-01","cited_by_count":0,"area":null},{"id":"2601.21433","title":"Framing Instability in LLM Ethical Stance: Auditing Negation Sensitivity in Moral Dilemmas","created":"2026-01-29","cited_by_count":0,"area":null},{"id":"2602.02878","title":"Which course? Discourse! Teaching Discourse and Generation in the Era of LLMs","created":"2026-02-02","cited_by_count":0,"area":null},{"id":"2604.00586","title":"More Human, More Efficient: Aligning Annotations with Quantized SLMs","created":"2026-04-01","cited_by_count":0,"area":null},{"id":"2604.08425","title":"Learning Who Disagrees: Demographic Importance Weighting for Modeling Annotator Distributions with DiADEM","created":"2026-04-09","cited_by_count":0,"area":null},{"id":"2606.02911","title":"The Ghost Annotator: a Framework to Explore Human Label Variation in Content Moderation through Conformal Prediction","created":"2026-06-01","cited_by_count":0,"area":null},{"id":"2606.07897","title":"Pander Score: A Continuous Measure of Sycophancy as Epistemic Deference","created":"2026-06-05","cited_by_count":0,"area":null},{"id":"2606.12411","title":"Context-Driven Incremental Compression for Multi-Turn Dialogue Generation","created":"2026-06-10","cited_by_count":0,"area":null},{"id":"2609.01139","title":"Does task decomposition improve automatic NLG evaluation?","created":"2026-09-01","cited_by_count":0,"area":null},{"id":"2609.06806","title":"Train Smarter, Not Harder: Switching Signal-Guided Training in Active Learning","created":"2026-09-06","cited_by_count":0,"area":null},{"id":"2609.15194","title":"Semiotic Relations and Proof Methods: A Cross-Genre Study of Argument Structure with Large Language Models","created":"2026-09-14","cited_by_count":0,"area":null},{"id":"2609.24629","title":"Augmented Hypothesis Testing with Persona-Based LLM Simulations","created":"2026-09-21","cited_by_count":0,"area":null},{"id":"2609.28026","title":"Evaluating Feedback Focus and Pedagogical Adaptivity in LLM-Generated Feedback on Student Writing","created":"2026-09-23","cited_by_count":0,"area":null},{"id":"2609.31857","title":"LLM Judge Validation Under Sparse Overlap: From Inference to Design","created":"2026-09-25","cited_by_count":0,"area":null},{"id":"2610.00007","title":"On-Device Named-Entity Recognition: A Deployability Study of Accuracy, Cost, Reliability, and Confidence","created":"2026-07-09","cited_by_count":0,"area":null},{"id":"2610.10918","title":"Large Language Models for Machine Translation Quality Annotation: Humans and Models Are Both Challenged","created":"2026-10-07","cited_by_count":0,"area":null},{"id":"2610.19992","title":"SoK: Grading Open-Text Legal Answers, from Law School Exams to Trustworthy Rubric Judges","created":"2026-10-14","cited_by_count":0,"area":null}],"next_cursor":null}