Multi-Agent Debate Technique
Multi-Agent Debate has agents take opposing viewpoints on complex problems, then converge on a well-reasoned solution. Models review each other's work, provide critique, and synthesize perspectives. This technique improves accuracy on complex reasoning tasks 35.9% relative reduction in hallucination on HaluEval, reduces bias through diverse perspectives, and increases solution robustness through deliberation. Council Mode achieves 7.8-point improvement on TruthfulQA vs. best individual model; collaborative process corrects errors 83% of the time when initial answers disagree.
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