Self-Distilled Agentic Reinforcement Learning

Zhengxi Lu, Zhiyuan Yao, Zhuowen Han +8

Reinforcement learning (RL) has emerged as a central paradigm for post-training LLM agents, yet its trajectory-level reward signal provides only coarse supervision for long-horizon…