RetireOPD: Self-Retiring On-Policy Distillation for Agentic Reinforcement Learning Paper • 2609.20784 • Published 4 days ago • 39
Reflect, Revise, Reuse: Training-Free Skill Evolution for GUI Agents Paper • 2609.17653 • Published 6 days ago • 37
RetireOPD: Self-Retiring On-Policy Distillation for Agentic Reinforcement Learning Paper • 2609.20784 • Published 4 days ago • 39
Reflect, Revise, Reuse: Training-Free Skill Evolution for GUI Agents Paper • 2609.17653 • Published 6 days ago • 37
PaperGym: Rubric-Centered Evolution for Research-Plan Generation Paper • 2608.31119 • Published 21 days ago • 33
PaperGym: Rubric-Centered Evolution for Research-Plan Generation Paper • 2608.31119 • Published 21 days ago • 33
Agent-G$^2$: Gaussian Guidance for Agentic Reinforcement Learning Paper • 2608.23318 • Published 28 days ago • 32
Agent-G^2: Gaussian Guidance for Agentic Reinforcement Learning Paper • 2608.23318 • Published 28 days ago • 32
EnvACE: Internalizing Environment Dynamics via World Rehearsal for Agentic Reinforcement Learning Paper • 2608.06197 • Published Aug 6 • 47
AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning Paper • 2608.05987 • Published Aug 6 • 102
Distill Where You Fail: Recovering Learning Signals of Negative RL-Groups from Adaptive Teacher Guidance Paper • 2608.00782 • Published Aug 1 • 18
Distill Where You Fail: Recovering Learning Signals of Negative RL-Groups from Adaptive Teacher Guidance Paper • 2608.00782 • Published Aug 1 • 18
VAD: Attributing Visual Evidence for Target Reconstruction in Multimodal On-Policy Distillation Paper • 2607.28590 • Published Jul 30 • 46
SkillRise: Agentic Reinforcement Learning for Cross-Task Skill Evolution Paper • 2607.26784 • Published Jul 29 • 29
SkillRise: Agentic Reinforcement Learning for Cross-Task Skill Evolution Paper • 2607.26784 • Published Jul 29 • 29
SEED: Self-Evolving On-Policy Distillation for Agentic Reinforcement Learning Paper • 2607.14777 • Published Jul 16 • 104
OPID: On-Policy Skill Distillation for Agentic Reinforcement Learning Paper • 2606.26790 • Published Jun 25 • 59
Qwen-AgentWorld: Language World Models for General Agents Paper • 2606.24597 • Published Jun 23 • 164