Why Multi-Agent Orchestration Collapses
jiqizhixin · x · 2026-07-14
Researchers from Nanjing University frame multi-agent orchestration as a tug-of-war between "task completion" and "information overload," analyzing why intelligent AI agents fail when collaborating.
They propose Inverse Workflow Generation (IWG) to construct more complex, verifiable benchmarks. Their analysis reveals a "Reasoning Trap": highly capable reasoning models may experience performance collapse when acting as an orchestrator due to context compression. The authors also introduce an entropy dynamics framework to quantify system stability and performance collapse, providing physical intuition for designing more robust multi-agent systems.
- Paper: arXiv:2606.01351
- Code: NJUNLP/orchestratorentropy
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