{"total":32,"rows":[{"id":"2409.12917","title":"Training Language Models to Self-Correct via Reinforcement Learning","created":"2024-09-19","cited_by_count":426,"area":"lr"},{"id":"2409.12183","title":"To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning","created":"2024-09-18","cited_by_count":263,"area":"lr"},{"id":"2310.15164","title":"LINC: A Neurosymbolic Approach for Logical Reasoning by Combining Language Models with First-Order Logic Provers","created":"2023-10-23","cited_by_count":168,"area":"lr"},{"id":"2410.02089","title":"RLEF: Grounding Code LLMs in Execution Feedback with Reinforcement Learning","created":"2024-10-02","cited_by_count":151,"area":"lr"},{"id":"2501.11425","title":"Agent-R: Training Language Model Agents to Reflect via Iterative Self-Training","created":"2025-01-20","cited_by_count":82,"area":"lr"},{"id":"2311.11797","title":"Igniting Language Intelligence: The Hitchhiker's Guide From Chain-of-Thought Reasoning to Language Agents","created":"2023-11-20","cited_by_count":72,"area":"lr"},{"id":"2501.02497","title":"A Survey of Test-Time Compute: From Intuitive Inference to Deliberate Reasoning","created":"2025-01-05","cited_by_count":40,"area":"lr"},{"id":"2504.10478","title":"Weight Ensembling Improves Reasoning in Language Models","created":"2025-04-14","cited_by_count":38,"area":"lr"},{"id":"2308.08784","title":"CodeCoT: Tackling Code Syntax Errors in CoT Reasoning for Code Generation","created":"2023-08-17","cited_by_count":29,"area":"lr"},{"id":"2506.08379","title":"Reinforce LLM Reasoning through Multi-Agent Reflection","created":"2025-06-10","cited_by_count":27,"area":"lr"},{"id":"2412.15118","title":"Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation","created":"2024-12-19","cited_by_count":21,"area":"lr"},{"id":"2504.13828","title":"Generative AI Act II: Test Time Scaling Drives Cognition Engineering","created":"2025-04-18","cited_by_count":15,"area":"lr"},{"id":"2406.10834","title":"Exposing the Achilles' Heel: Evaluating LLMs Ability to Handle Mistakes in Mathematical Reasoning","created":"2024-06-16","cited_by_count":13,"area":"lr"},{"id":"2506.04894","title":"ICPC-Eval: Probing the Frontiers of LLM Reasoning with Competitive Programming Contests","created":"2025-06-05","cited_by_count":13,"area":"lr"},{"id":"2412.15305","title":"Tree-of-Code: A Tree-Structured Exploring Framework for End-to-End Code Generation and Execution in Complex Task Handling","created":"2024-12-19","cited_by_count":11,"area":"lr"},{"id":"2511.04662","title":"VeriCoT: Neuro-symbolic Chain-of-Thought Validation via Logical Consistency Checks","created":"2025-11-06","cited_by_count":11,"area":"lr"},{"id":"2411.05010","title":"Scattered Forest Search: Smarter Code Space Exploration with LLMs","created":"2024-10-22","cited_by_count":10,"area":"lr"},{"id":"2312.15960","title":"MoTCoder: Elevating Large Language Models with Modular of Thought for Challenging Programming Tasks","created":"2023-12-26","cited_by_count":9,"area":"lr"},{"id":"2502.19414","title":"Can Language Models Falsify? Evaluating Algorithmic Reasoning with Counterexample Creation","created":"2025-02-26","cited_by_count":7,"area":"lr"},{"id":"2505.18555","title":"Unraveling Misinformation Propagation in LLM Reasoning","created":"2025-05-24","cited_by_count":6,"area":"lr"},{"id":"2605.11556","title":"Hindsight Hint Distillation: Scaffolded Reasoning for SWE Agents from CoT-free Answers","created":"2026-05-12","cited_by_count":5,"area":"lr"},{"id":"2403.16921","title":"PropTest: Automatic Property Testing for Improved Visual Programming","created":"2024-03-25","cited_by_count":4,"area":"lr"},{"id":"2502.18487","title":"AuPair: Golden Example Pairs for Code Repair","created":"2025-02-12","cited_by_count":3,"area":"lr"},{"id":"2607.02436","title":"Reasoning effort, not tool access, buys first-try reliability in agentic code generation: an observational study","created":"2026-07-02","cited_by_count":2,"area":"lr"},{"id":"2601.07180","title":"Structured Reasoning for Large Language Models","created":"2026-01-12","cited_by_count":1,"area":"lr"},{"id":"2602.13962","title":"CodeGlance: Understanding Code Reasoning Challenges in LLMs through Multi-Dimensional Feature Analysis","created":"2026-02-15","cited_by_count":1,"area":"lr"},{"id":"2601.21469","title":"Adaptive Confidence Gating in Multi-Agent Collaboration for Efficient and Optimized Code Generation","created":"2026-01-29","cited_by_count":0,"area":"lr"},{"id":"2604.27960","title":"LLMs as ASP Programmers: Self-Correction Enables Task-Agnostic Nonmonotonic Reasoning","created":"2026-04-30","cited_by_count":0,"area":"lr"},{"id":"2605.30052","title":"REPOT: Recoverable Program-of-Thought via Checkpoint Repair","created":"2026-05-28","cited_by_count":0,"area":"lr"},{"id":"2609.12757","title":"GraphAHA: Graph-Based Adaptive Search with Heterogeneous Actions for Test-Time Code Generation","created":"2026-09-11","cited_by_count":0,"area":"lr"},{"id":"2609.22878","title":"ISA-Bench: A Benchmark for Computational Reasoning Across Instruction Set Architectures","created":"2026-09-19","cited_by_count":0,"area":"lr"},{"id":"2610.05170","title":"Verification Trap: Understanding Test-Time Selection Failures under False Premises in Code Generation","created":"2026-10-04","cited_by_count":0,"area":"lr"}],"next_cursor":null}