Not Every Agent Needs the Strongest Model: Unified Prompt-Model Optimization for Heterogeneous LLM-based Multi-Agent Systems
4.40T1 sourcearXiv cs.MA
Source record
Published by arXiv cs.MA (T1 source). The original is at https://arxiv.org/abs/2610.31743.
Pipeline notes
The summary and note below are generated by the signal pipeline — they are Beyond Desk’s reading, not quotations from the source.
SummaryUniMASO jointly optimizes role-specific prompts and model assignments in multi-agent systems using local, downstream, and global feedback. Its cost-aware Pareto search and topology-aware co-evolution reportedly preserve task performance while reducing token-weighted deployment cost across five benchmarks and execution topologies.
Why it mattersProvides a tested method for assigning different models to agent roles and optimizing prompts together, with reported cost reductions and public implementation code.
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