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W. Jin

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Preprint Aug 2026

OptiMAS: Automatically Optimize Multi-Agent System

This work presents OptiMAS, a task-agnostic agentic optimizer that leverages textual interaction trajectories and task feedback as loss signals for end-to-end MAS evolution and sustains performance improvement over extended optimization horizons.

Yuxin Cheng, Chang Liu, Hanxin Yu et al. · 0 citations

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