{"total":52,"rows":[{"id":"2406.00515","title":"A Survey on Large Language Models for Code Generation","created":"2024-06-01","cited_by_count":658,"area":null},{"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":"2410.10934","title":"Agent-as-a-Judge: Evaluate Agents with Agents","created":"2024-10-14","cited_by_count":238,"area":"agents"},{"id":"2403.09032","title":"CodeUltraFeedback: An LLM-as-a-Judge Dataset for Aligning Large Language Models to Coding Preferences","created":"2024-03-14","cited_by_count":57,"area":"alignment"},{"id":"2504.12522","title":"Evaluating the Diversity and Quality of LLM Generated Content","created":"2025-04-16","cited_by_count":51,"area":"lr"},{"id":"2410.02184","title":"CodeJudge: Evaluating Code Generation with Large Language Models","created":"2024-10-03","cited_by_count":44,"area":null},{"id":"2507.10535","title":"CodeJudgeBench: Benchmarking LLM-as-a-Judge for Coding Tasks","created":"2025-07-14","cited_by_count":33,"area":null},{"id":"2307.12966","title":"Aligning Large Language Models with Human: A Survey","created":"2023-07-24","cited_by_count":32,"area":"alignment"},{"id":"2502.12468","title":"MCTS-Judge: Test-Time Scaling in LLM-as-a-Judge for Code Correctness Evaluation","created":"2025-02-18","cited_by_count":32,"area":"lr"},{"id":"2408.10718","title":"CodeJudge-Eval: Can Large Language Models be Good Judges in Code Understanding?","created":"2024-08-20","cited_by_count":30,"area":null},{"id":"2506.17335","title":"LMR-BENCH: Evaluating LLM Agent's Ability on Reproducing Language Modeling Research","created":"2025-06-19","cited_by_count":29,"area":"agents"},{"id":"2409.15154","title":"RMCBench: Benchmarking Large Language Models' Resistance to Malicious Code","created":"2024-09-23","cited_by_count":28,"area":"safety"},{"id":"2504.18838","title":"Toward Generalizable Evaluation in the LLM Era: A Survey Beyond Benchmarks","created":"2025-04-26","cited_by_count":28,"area":null},{"id":"2311.14904","title":"LLM-Assisted Code Cleaning For Training Accurate Code Generators","created":"2023-11-25","cited_by_count":27,"area":null},{"id":"2503.01245","title":"Large Language Models for Code Generation: A Comprehensive Survey of Challenges, Techniques, Evaluation, and Applications","created":"2025-03-03","cited_by_count":26,"area":null},{"id":"2401.14698","title":"Under the Surface: Tracking the Artifactuality of LLM-Generated Data","created":"2024-01-26","cited_by_count":24,"area":"synth"},{"id":"2310.20158","title":"GAR-meets-RAG Paradigm for Zero-Shot Information Retrieval","created":"2023-10-31","cited_by_count":18,"area":null},{"id":"2505.16222","title":"Don't Judge Code by Its Cover: Exploring Biases in LLM Judges for Code Evaluation","created":"2025-05-22","cited_by_count":18,"area":null},{"id":"2508.03550","title":"Beyond the Surface: Enhancing LLM-as-a-Judge Alignment with Human via Internal Representations","created":"2025-08-05","cited_by_count":15,"area":"alignment"},{"id":"2408.11081","title":"What can Large Language Models Capture about Code Functional Equivalence?","created":"2024-08-20","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":"2502.15025","title":"Is Relevance Propagated from Retriever to Generator in RAG?","created":"2025-02-20","cited_by_count":11,"area":"rag"},{"id":"2503.00691","title":"How Diversely Can Language Models Solve Problems? Exploring the Algorithmic Diversity of Model-Generated Code","created":"2025-03-02","cited_by_count":11,"area":null},{"id":"2501.05396","title":"FairCoder: Probing LLM Bias in High-Stakes Decision Making via Coding Tasks","created":"2025-01-09","cited_by_count":9,"area":null},{"id":"2406.10882","title":"SCAR: Data Selection via Style Consistency-Aware Response Ranking for Efficient Instruction-Tuning of Large Language Models","created":"2024-06-16","cited_by_count":6,"area":null},{"id":"2504.13472","title":"CodeVisionary: An Agent-based Framework for Evaluating Large Language Models in Code Generation","created":"2025-04-18","cited_by_count":6,"area":"agents"},{"id":"2602.19594","title":"ISO-Bench: Can Coding Agents Optimize Real-World Inference Workloads?","created":"2026-02-23","cited_by_count":6,"area":"agents"},{"id":"2405.14753","title":"A Transformer-Based Approach for Smart Invocation of Automatic Code Completion","created":"2024-05-23","cited_by_count":5,"area":null},{"id":"2407.04831","title":"Code Hallucination","created":"2024-07-05","cited_by_count":5,"area":null},{"id":"2408.13745","title":"DOCE: Finding the Sweet Spot for Execution-Based Code Generation","created":"2024-08-25","cited_by_count":4,"area":null},{"id":"2408.15630","title":"CodeSift: An LLM-Based Reference-Less Framework for Automatic Code Validation","created":"2024-08-28","cited_by_count":4,"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":"2510.10460","title":"Understanding and Bridging the Planner-Coder Gap: A Systematic Study on the Robustness of Multi-Agent Systems for Code Generation","created":"2025-10-12","cited_by_count":4,"area":"agents"},{"id":"2511.07017","title":"Benchmarking LLMs for Fine-Grained Code Review with Enriched Context in Practice","created":"2025-11-10","cited_by_count":4,"area":null},{"id":"2604.16790","title":"Bias in the Loop: Auditing LLM-as-a-Judge for Software Engineering","created":"2026-04-18","cited_by_count":4,"area":null},{"id":"2305.19915","title":"Source Code Data Augmentation for Deep Learning: A Survey","created":"2023-05-31","cited_by_count":3,"area":null},{"id":"2409.17166","title":"ScriptSmith: A Unified LLM Framework for Enhancing IT Operations via Automated Bash Script Generation, Assessment, and Refinement","created":"2024-09-12","cited_by_count":3,"area":null},{"id":"2411.00005","title":"Mastering the Craft of Data Synthesis for CodeLLMs","created":"2024-10-16","cited_by_count":3,"area":"synth"},{"id":"2502.07835","title":"Bridging LLM-Generated Code and Requirements: Reverse Generation technique and SBC Metric for Developer Insights","created":"2025-02-11","cited_by_count":3,"area":null},{"id":"2505.19502","title":"CODE-DITING: A Reasoning-Based Metric for Functional Alignment in Code Evaluation","created":"2025-05-26","cited_by_count":2,"area":"lr"},{"id":"2506.04019","title":"CETBench: A Novel Dataset constructed via Transformations over Programs for Benchmarking LLMs for Code-Equivalence Checking","created":"2025-06-04","cited_by_count":1,"area":null},{"id":"2506.11237","title":"LLM-as-a-Judge for Reference-less Automatic Code Validation and Refinement for Natural Language to Bash in IT Automation","created":"2025-06-12","cited_by_count":1,"area":null},{"id":"2510.23169","title":"MATCH: Task-Driven Code Evaluation through Contrastive Learning","created":"2025-10-27","cited_by_count":1,"area":null},{"id":"2512.20159","title":"Benchmarking Code LLM-as-a-Judge via Constrained Perturbation and Calibration","created":"2025-12-23","cited_by_count":1,"area":null},{"id":"2605.15416","title":"Margin-Adaptive Confidence Ranking for Reliable LLM Judgement","created":"2026-05-14","cited_by_count":1,"area":null},{"id":"2502.18874","title":"Learning to Align Multi-Faceted Evaluation: A Unified and Robust Framework","created":"2025-02-26","cited_by_count":0,"area":null},{"id":"2510.09898","title":"Learning Bug Context for PyTorch-to-JAX Translation with LLMs","created":"2025-10-10","cited_by_count":0,"area":null},{"id":"2512.16272","title":"Beyond Blind Spots: Analytic Hints for Mitigating LLM-Based Evaluation Pitfalls","created":"2025-12-18","cited_by_count":0,"area":null},{"id":"2608.07038","title":"Beyond Text Matching: Towards Reference-Free Evaluation for Human-Oriented Binary Reverse Engineering","created":"2026-08-07","cited_by_count":0,"area":null},{"id":"2610.04737","title":"PyINE: A Framework for Scalable Elicitation and Oversight via Code Execution","created":"2026-10-03","cited_by_count":0,"area":"lr"},{"id":"2610.13361","title":"AgentSWE: Can Coding Agents Build the Agent You Actually Want?","created":"2026-10-09","cited_by_count":0,"area":"agents"}],"next_cursor":null}