Reliable Disagreement Resolution in Multi-Agent Systems

Identify robust disagreement-resolution mechanisms for multi-agent LLM systems that aggregate evidence-backed critiques and yield reliable consensus without amplifying correlated errors or miscalibrated aggregation.

Background

Multi-agent designs promise specialization and cross-checking, but naïve debate or voting can magnify shared blind spots and produce unstable conclusions. Effective governance requires protocols that tie critiques to evidence and calibrate aggregation.

Solving this problem would enable scalable collaboration among agents with bounded privileges, clearer escalation paths, and more trustworthy outcomes in complex workflows.