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News/StepPO: Step-Aligned Policy Optimization for Agentic Reinforcement Learning
arxiv
PublishedJune 2, 2026 at 4:00 AM

StepPO: Step-Aligned Policy Optimization for Agentic Reinforcement Learning

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arXiv:2604.18401v2 Announce Type: replace Abstract: Agentic reinforcement learning (RL) is emerging as a critical post-training paradigm for improving LLM agent capabilities. Existing RL algorithms for LLMs largely follow the token-centric paradigm as in RLHF and RLVR, where tokens serve as the basi

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