Author

Lang Feng

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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