{"total":19,"rows":[{"id":"2512.02472","title":"Guided Self-Evolving LLMs with Minimal Human Supervision","created":"2025-12-02","cited_by_count":35,"area":null},{"id":"2510.02453","title":"How to Train Your Advisor: Steering Black-Box LLMs with Advisor Models","created":"2025-10-02","cited_by_count":24,"area":null},{"id":"2506.18110","title":"RL for Reasoning by Adaptively Revealing Rationales","created":"2025-06-22","cited_by_count":16,"area":null},{"id":"2606.16062","title":"Auditing Reward Hackability in Code RL Training Environments","created":"2026-06-14","cited_by_count":5,"area":null},{"id":"2601.15609","title":"When Sharpening Becomes Collapse: Sampling Bias and Semantic Coupling in RL with Verifiable Rewards","created":"2026-01-22","cited_by_count":4,"area":null},{"id":"2607.07674","title":"Max Out GRPO Signal: Adaptive Trace Prefix Control for Hard Reasoning Problems","created":"2026-07-08","cited_by_count":3,"area":null},{"id":"2606.05606","title":"Cross-Epoch Adaptive Rollout Optimization for RL Post-Training","created":"2026-06-04","cited_by_count":2,"area":null},{"id":"2607.26253","title":"Early Verdicts, Better Budgets: Sequential Adaptive Rollout Allocation for Compute-Efficient RLVR","created":"2026-07-28","cited_by_count":2,"area":null},{"id":"2606.03087","title":"Learning to Solve, Forgetting to Retain: Correct-Set Turnover in RLVR","created":"2026-06-02","cited_by_count":1,"area":null},{"id":"2608.26582","title":"J-Zero: Unified Challenger--Solver--Judge Self-Evolution from Zero Data","created":"2026-08-27","cited_by_count":1,"area":null},{"id":"2609.00768","title":"Learning What to Practice: Diagnosis-Guided Self-Evolution for Language Models","created":"2026-09-01","cited_by_count":1,"area":null},{"id":"2609.40115","title":"Unlearnable, or Unmeasured? On the Reliability of Difficulty Labels in RLVR","created":"2026-09-30","cited_by_count":1,"area":null},{"id":"2509.25240","title":"HAMMER: Hamiltonian Curiosity Augmented Large Language Model Reinforcement","created":"2025-09-25","cited_by_count":0,"area":null},{"id":"2510.04033","title":"A global log for medical AI","created":"2025-10-05","cited_by_count":0,"area":null},{"id":"2607.04412","title":"LLM-as-a-Tutor: Policy-Aware Prompt Adaptation for Non-Verifiable RL","created":"2026-07-05","cited_by_count":0,"area":null},{"id":"2608.05797","title":"Predicting Task Difficulty Without Rollouts","created":"2026-08-06","cited_by_count":0,"area":null},{"id":"2609.04735","title":"Training Large Language Models for Small-Molecule Design with Synthetic Task Scaling","created":"2026-09-04","cited_by_count":0,"area":null},{"id":"2609.36830","title":"Where Does Staleness Accumulate? Pool Aware Effective Staleness Control for Asynchronous RL in LLM Post-Training","created":"2026-09-29","cited_by_count":0,"area":null},{"id":"2610.14913","title":"Bridging Risk Approximation Gaps in Model Predictive Task Sampling via In-Context Modeling","created":"2026-10-10","cited_by_count":0,"area":null}],"next_cursor":null}