{"total":33,"rows":[{"id":"2510.18927","title":"BAPO: Stabilizing Off-Policy Reinforcement Learning for LLMs via Balanced Policy Optimization with Adaptive Clipping","created":"2025-10-21","cited_by_count":47,"area":null},{"id":"2509.16679","title":"Reinforcement Learning Meets Large Language Models: A Survey of Advancements and Applications Across the LLM Lifecycle","created":"2025-09-20","cited_by_count":35,"area":null},{"id":"2509.25849","title":"Knapsack RL: Unlocking Exploration of LLMs via Optimizing Budget Allocation","created":"2025-09-30","cited_by_count":22,"area":null},{"id":"2510.06062","title":"When Importance Sampling Misallocates Credit: Asymmetric Ratios for Outcome-Supervised RL","created":"2025-10-07","cited_by_count":21,"area":null},{"id":"2509.21044","title":"Reinforcement Learning Fine-Tuning Enhances Activation Intensity and Diversity in the Internal Circuitry of LLMs","created":"2025-09-25","cited_by_count":9,"area":null},{"id":"2511.00796","title":"AReaL-Hex: Accommodating Asynchronous RL Training over Heterogeneous GPUs","created":"2025-11-02","cited_by_count":9,"area":null},{"id":"2601.02075","title":"MDAgent2: Large Language Model for Code Generation and Knowledge Q&A in Molecular Dynamics","created":"2026-01-05","cited_by_count":7,"area":null},{"id":"2510.17881","title":"POPI: Personalizing LLMs via Optimized Natural Language Preference Inference","created":"2025-10-17","cited_by_count":6,"area":null},{"id":"2602.10161","title":"Omni-Safety under Cross-Modality Conflict: Vulnerabilities, Dynamics Mechanisms and Efficient Alignment","created":"2026-02-10","cited_by_count":6,"area":null},{"id":"2604.07941","title":"Large Language Model Post-Training: A Unified View of Off-Policy and On-Policy Learning","created":"2026-04-09","cited_by_count":6,"area":null},{"id":"2606.14502","title":"From Chatbot to Digital Colleague: The Paradigm Shift Toward Persistent Autonomous AI","created":"2026-06-12","cited_by_count":6,"area":null},{"id":"2603.01501","title":"GAC: Stabilizing Asynchronous RL Training for LLMs via Gradient Alignment Control","created":"2026-03-02","cited_by_count":5,"area":null},{"id":"2509.22613","title":"Benefits and Pitfalls of Reinforcement Learning for Language Model Planning: A Theoretical Perspective","created":"2025-09-26","cited_by_count":4,"area":null},{"id":"2606.09932","title":"When RL Fails after SFT: Rejuvenating Model Plasticity for Robust SFT-to-RL Handoff","created":"2026-06-07","cited_by_count":4,"area":null},{"id":"2511.21075","title":"Aligning LLMs with Biomedical Knowledge using Balanced Fine-Tuning","created":"2025-11-26","cited_by_count":3,"area":null},{"id":"2605.11775","title":"Entropy Polarity in Reinforcement Fine-Tuning: Direction, Asymmetry, and Control","created":"2026-05-12","cited_by_count":3,"area":null},{"id":"2601.15330","title":"ICPO: Illocution-Calibrated Policy Optimization for Multi-Turn Conversation","created":"2026-01-20","cited_by_count":2,"area":null},{"id":"2605.09640","title":"Overcoming Catastrophic Forgetting in Visual Continual Learning with Reinforcement Fine-Tuning","created":"2026-05-10","cited_by_count":2,"area":null},{"id":"2607.04332","title":"On the effectiveness of reward functions in reinforcement learning for confidence calibration of large language models","created":"2026-07-05","cited_by_count":2,"area":null},{"id":"2601.22648","title":"UCPO: Uncertainty-Aware Policy Optimization","created":"2026-01-30","cited_by_count":1,"area":null},{"id":"2602.10635","title":"OmniSapiens: A Foundation Model for Social Behavior Processing via Heterogeneity-Aware Relative Policy Optimization","created":"2026-02-11","cited_by_count":1,"area":null},{"id":"2602.11570","title":"PRIME: A Process-Outcome Alignment Benchmark for Verifiable Reasoning in Mathematics and Engineering","created":"2026-02-12","cited_by_count":1,"area":null},{"id":"2602.19178","title":"EMAD: Evidence-Centric Grounded Multimodal Diagnosis for Alzheimer's Disease","created":"2026-02-22","cited_by_count":1,"area":null},{"id":"2605.30478","title":"Improving Small Language Models for Code Generation with Reinforcement Learning from Verification Feedback","created":"2026-05-28","cited_by_count":1,"area":null},{"id":"2605.31058","title":"Combinatorial Synthesis: Scaling Code RLVR via Atomic Decomposition and Recombination","created":"2026-05-29","cited_by_count":1,"area":null},{"id":"2601.22532","title":"Demystifying Design Choices of Reinforcement Fine-tuning: A Batched Contextual Bandit Learning Perspective","created":"2026-01-30","cited_by_count":0,"area":null},{"id":"2602.00307","title":"Autonomous Data Processing using Meta-Agents","created":"2026-01-30","cited_by_count":0,"area":null},{"id":"2603.06397","title":"Efficient, Property-Aligned Fan-Out Retrieval via RL-Compiled Diffusion","created":"2026-03-06","cited_by_count":0,"area":null},{"id":"2604.17543","title":"PoliLegalLM: A Technical Report on a Large Language Model for Political and Legal Affairs","created":"2026-04-19","cited_by_count":0,"area":null},{"id":"2605.31034","title":"Annealed Softmax Greedy in Many-Armed Bayesian Bandits","created":"2026-05-29","cited_by_count":0,"area":null},{"id":"2608.07547","title":"Learning an Interior Layout Policy in a Domain Specific Language Action Space","created":"2026-07-31","cited_by_count":0,"area":null},{"id":"2609.26355","title":"PACT: From Credit Assignment to Critic Alignment","created":"2026-09-22","cited_by_count":0,"area":null},{"id":"2610.04261","title":"Playing social deduction games with reinforcement fine-tuned large language models","created":"2026-10-03","cited_by_count":0,"area":null}],"next_cursor":null}