Author

Jinghan Li

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Jun 2026

Experience Augmented Policy Optimization for LLM Reasoning

This work proposes Experience-Augmented Policy Optimization (EAPO), which leverages a prior RL-optimized policy as an action-level experience prior and selectively injects experience at critical decision points during rollout to ensure stable and unbiased learning from experience-augmented rollouts.

Jinda Lu, Kexin Huang, Junkang Wu et al. · arXiv.org · 2 citations