{"total":22,"rows":[{"id":"2505.03335","title":"Absolute Zero: Reinforced Self-play Reasoning with Zero Data","created":"2025-05-06","cited_by_count":344,"area":"lr"},{"id":"2509.08827","title":"A Survey of Reinforcement Learning for Large Reasoning Models","created":"2025-09-10","cited_by_count":180,"area":"lr"},{"id":"2505.12370","title":"Enhancing Visual Grounding for GUI Agents via Self-Evolutionary Reinforcement Learning","created":"2025-05-18","cited_by_count":81,"area":"lr"},{"id":"2505.23433","title":"Diversity-Aware Policy Optimization for Large Language Model Reasoning","created":"2025-05-29","cited_by_count":41,"area":"lr"},{"id":"2505.03469","title":"Long-Short Chain-of-Thought Mixture Supervised Fine-Tuning Eliciting Efficient Reasoning in Large Language Models","created":"2025-05-06","cited_by_count":39,"area":"lr"},{"id":"2510.07364","title":"Base Models Know How to Reason, Thinking Models Learn When","created":"2025-10-08","cited_by_count":27,"area":"lr"},{"id":"2507.09662","title":"Towards Concise and Adaptive Thinking in Large Reasoning Models: A Survey","created":"2025-07-13","cited_by_count":18,"area":"lr"},{"id":"2510.04474","title":"DRPO: Efficient Reasoning via Decoupled Reward Policy Optimization","created":"2025-10-06","cited_by_count":16,"area":"lr"},{"id":"2505.18536","title":"Reinforcement Fine-Tuning Powers Reasoning Capability of Multimodal Large Language Models","created":"2025-05-24","cited_by_count":14,"area":"lr"},{"id":"2507.14683","title":"MiroMind-M1: An Open-Source Advancement in Mathematical Reasoning via Context-Aware Multi-Stage Policy Optimization","created":"2025-07-19","cited_by_count":12,"area":"lr"},{"id":"2510.08308","title":"First Try Matters: Revisiting the Role of Reflection in Reasoning Models","created":"2025-10-09","cited_by_count":12,"area":"lr"},{"id":"2505.15311","title":"Trajectory Bellman Residual Minimization: A Simple Value-Based Method for LLM Reasoning","created":"2025-05-21","cited_by_count":11,"area":"lr"},{"id":"2505.16142","title":"RLKD: Distilling LLMs' Reasoning via Reinforcement Learning","created":"2025-05-22","cited_by_count":11,"area":"lr"},{"id":"2510.11620","title":"Enhancing Long Chain-of-Thought Reasoning through Multi-Path Plan Aggregation","created":"2025-10-13","cited_by_count":11,"area":"lr"},{"id":"2510.11056","title":"From Reasoning LLMs to BERT: A Two-Stage Distillation Framework for Search Relevance","created":"2025-10-13","cited_by_count":7,"area":"lr"},{"id":"2505.12151","title":"Reasoning Large Language Model Errors Arise from Hallucinating Critical Problem Features","created":"2025-05-17","cited_by_count":6,"area":"lr"},{"id":"2601.19928","title":"Towards a Mechanistic Understanding of Large Reasoning Models: A Survey of Training, Inference, and Failures","created":"2026-01-11","cited_by_count":6,"area":"lr"},{"id":"2507.01327","title":"Reasoner for Real-World Event Detection: Scaling Reinforcement Learning via Adaptive Perplexity-Aware Sampling Strategy","created":"2025-07-02","cited_by_count":3,"area":"lr"},{"id":"2605.30832","title":"SLAT: Segment-Level Adaptive Trimming for Efficient CoT Reasoning","created":"2026-05-29","cited_by_count":1,"area":"lr"},{"id":"2508.12897","title":"RAJ-PGA: Reasoning-Activated Jailbreak and Principle-Guided Alignment Framework for Large Reasoning Models","created":"2025-08-18","cited_by_count":0,"area":"lr"},{"id":"2602.04919","title":"Gradually Compacting Large Language Models for Reasoning Like a Boiling Frog","created":"2026-02-04","cited_by_count":0,"area":"lr"},{"id":"2605.31446","title":"Fine-grained Verification via Diagnostic Reasoning Supervision for Aspect Sentiment Triplet Extraction","created":"2026-05-29","cited_by_count":0,"area":"lr"}],"next_cursor":null}