Author

Zheng Lian

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#natural language process... Preprint Oct 2026

RSIPO: Recursive Self-Improving Policy Optimization for Agentic Reinforcement Learning via Skill-Policy Co-Evolution

Recent focus in agentic reinforcement learning (RL) seeks to improve credit assignment in long-horizon tasks. One promising direction combines reinforcement learning with verifiable rewards (RLVR) and on-policy self-distillation (OPSD), integrating trajectory-level advantages with dense token-level supervision. This li...

Fan Zhang, Hao Wu, Jin-Yang Wu et al. · 0 citations

Jul 2026

SEED: Self-Evolving On-Policy Distillation for Agentic Reinforcement Learning

SEED (SElf-Evolving On-Policy Distillation), a self-evolving framework that converts completed on-policy trajectories into training-time hindsight skills and distills their behavioral effect back into the policy model, is proposed.

Jinyang Wu, Shuo Yang, Zhengxi Lu et al. · arXiv.org · 7 citations