Waypoint-OPD: Transferring RL-Induced Policy Shifts via Gated On-Policy Distillation Paper • 2610.21601 • Published 8 days ago • 220
Waypoint-OPD: Transferring RL-Induced Policy Shifts via Gated On-Policy Distillation Paper • 2610.21601 • Published 8 days ago • 220
Waypoint-OPD: Transferring RL-Induced Policy Shifts via Gated On-Policy Distillation Paper • 2610.21601 • Published 8 days ago • 220
Rethinking Cross-Tokenizer On-Policy Distillation: From Alignment Coverage to Supervision Reliability Paper • 2610.08448 • Published 17 days ago • 110
Rethinking Cross-Tokenizer On-Policy Distillation: From Alignment Coverage to Supervision Reliability Paper • 2610.08448 • Published 17 days ago • 110
Rethinking Cross-Tokenizer On-Policy Distillation: From Alignment Coverage to Supervision Reliability Paper • 2610.08448 • Published 17 days ago • 110
Rethinking On-Policy Distillation of Large Language Models II: One Training Example Paper • 2609.04172 • Published Sep 3 • 99
ProRL: Effective Reinforcement Learning for Proactive Recommendation via Rectified Policy Gradient Estimation Paper • 2605.28293 • Published May 27 • 87
Efficient Agentic Reinforcement Learning with On-Policy Intrinsic Knowledge Boundary Enhancement Paper • 2605.26952 • Published May 26 • 12
DVAO: Dynamic Variance-adaptive Advantage Optimization for Multi-reward Reinforcement Learning Paper • 2605.25604 • Published May 25 • 49
DVAO: Dynamic Variance-adaptive Advantage Optimization for Multi-reward Reinforcement Learning Paper • 2605.25604 • Published May 25 • 49
DVAO: Dynamic Variance-adaptive Advantage Optimization for Multi-reward Reinforcement Learning Paper • 2605.25604 • Published May 25 • 49
Rethinking Generalization in Reasoning SFT: A Conditional Analysis on Optimization, Data, and Model Capability Paper • 2604.06628 • Published Apr 8 • 130
Beyond Stochastic Exploration: What Makes Training Data Valuable for Agentic Search Paper • 2604.08124 • Published Apr 9 • 4
FAQ: Mitigating Quantization Error via Regenerating Calibration Data with Family-Aware Quantization Paper • 2601.11200 • Published Jan 16
Beyond Stochastic Exploration: What Makes Training Data Valuable for Agentic Search Paper • 2604.08124 • Published Apr 9 • 4
Beyond Stochastic Exploration: What Makes Training Data Valuable for Agentic Search Paper • 2604.08124 • Published Apr 9 • 4