Remember and Reweight: Enhancing Multi-Agent Debate with Experience Memory and Confidence Estimation
This work proposes R$^2$-MAD (Remember and Reweight for Multi-Agent Debate), a framework that equips agents with an experience memory accumulated from past debates that achieves consistent improvements over existing single-agent and MAD baselines.
Xuan-Fa Jin, Zhijian Ma, Yong-Cheng Zeng et al.
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