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papersTODAY 04:00 UTC

arXiv Paper Proposes Human-Grounded Diagnosis of Multi-Agent LLM Collaboration

A new arXiv paper argues that judging multi-agent LLM systems only by their final answers misses how those systems actually reach their results. The authors propose a diagnostic method grounded in human group research to distinguish process losses from assembly bonuses when LLM teams collaborate. This matters both for building better agent pipelines and for using LLM groups as stand-ins for human group behavior.

agents/multi-agent/evaluation/research