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News/When Does Multi-Agent RL Improve LLM Workflows? Workflow, Scale, and Policy-Sharing Tradeoffs
arxiv
PublishedMay 26, 2026 at 4:00 AM
—neutral

When Does Multi-Agent RL Improve LLM Workflows? Workflow, Scale, and Policy-Sharing Tradeoffs

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arxiv.orgfull article ↗
Read on arxiv→
Publisher summary· verbatim

arXiv:2605.24202v1 Announce Type: new Abstract: Multi-agent LLM workflows route inference through specialized roles to lift end-task accuracy, but jointly training those roles with reinforcement learning is unstable in ways that are poorly understood. We study when end-to-end RL training of multi-ag

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Discussion
Mentioned models
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  • 01
    LLM
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arxiv
Read original ↗All from arxiv →
Tags
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#multi-agent#reinforcement-learning#workflow#stability

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Mentioned models
01
  • 01
    LLM
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#multi-agent#reinforcement-learning#workflow#stability
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Originally published on arxiv ↗
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