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Zi-Yun Xiong

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Preprint Sep 2026

SRPO: Setwise Relative Policy Optimization for Multi-Agent Systems

Multi-agent systems enable complex reasoning and tool use by coordinating agents that divide roles and refine candidate solutions. Existing methods typically update individual agent responses or treat a complete trajectory as one training example. However, these methods may produce misleading policy updates because the...

Sheng-Tian Yang, Zi-Yun Xiong, Yu Li et al. · 0 citations

#artificial intelligence Preprint Sep 2026

SRPO: Setwise Relative Policy Optimization for Multi-Agent LLMs

Multi-agent large language models solve complex tasks by coordinating several policies in a shared environment. However, existing reinforcement learning methods usually optimize each response or trajectory separately, even when several outputs jointly cause one state transition. Consequently, the update unit differs fr...

Sheng-Tian Yang, Zi-Yun Xiong, Yu Li et al. · 4 citations