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Co-RL: Unsupervised Reasoning Emerges from Diverse Cohort in Multi-agent RL

92 upvotes · 19 AUG 2026 · Yunhao Yang, Yuexin Bian, Yunjie Tian et al.

This paper introduces Co-RL, a framework for unsupervised multi-agent reinforcement learning that enables diverse and accurate reasoning in language and vision-language models. Practitioners can use Co-RL to improve their models' ability to reason and respond without relying on expensive ground-truth supervision.

multi-agent RLunsupervised learningreasoningreinforcement learninglanguage modelsvision-language models