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MetaAgent-X : Breaking the Ceiling of Automatic Multi-Agent Systems via End-to-End Reinforcement Learning

arXiv cs.AI ↗ · 2026-05-15 Cached

MetaAgent-X introduces an end-to-end reinforcement learning framework that jointly optimizes the design and execution of automatic multi-agent systems, overcoming the frozen-executor ceiling and achieving up to 21.7% gains over existing baselines.

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