HETEROGENEOUSSWARMS: Jointly Optimizing Model Roles and Weights for Multi-LLM Systems

Neural Information Processing Systems 

We propose HETEROGENEOUSSWARMS, an algorithm to design multi-LLM systems by jointly optimizing model roles and weights. We represent multi-LLM systems as directed acyclic graphs (DAGs) of LLMs with topological message passing for collaborative generation.

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