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Remember and Reweight: Enhancing Multi-Agent Debate with Experience Memory and Confidence Estimation
Multi-agent debate (MAD) improves the reasoning capabilities of large language models by having multiple agents iteratively refine their responses through discussion. However, MAD suffers from a critical vulnerability known as shared misconception: when a majority of agents initially converge on an
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