Author

Linji Hao

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Preprint Aug 2026

AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning

This work proposes AgentOPSD, a critic-free, recursive method for turn-level credit assignment in agentic reinforcement learning that aggregates token-level teacher-student log-probability gaps into turn-level evidence and recursively updates a Bayesian belief state in log-odds space.

Zi-Han Wang, Zhengxi Lu, Zhiyuan Yao et al. · 1 citation