MAS-Orchestra: Understanding and Improving Multi-Agent Reasoning Through Holistic Orchestration and Controlled Benchmarks

MAS-Orchestra is a new framework for designing multi-agent systems that formulates orchestration as a function-calling reinforcement learning problem to enhance global reasoning and efficiency; alongside, MASBENCH provides a controlled benchmark to study under what conditions MAS outperform single-agent systems, revealing task-specific benefits and guiding improvements in public benchmarks.

Read the full article at arXiv cs.CL (NLP)

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