Papers with vanilla MAD

    1 papers
    Demystifying Multi-Agent Debate: The Role of Confidence and Diversity (2026.findings-acl)

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    Challenge: Multi-agent debate (MAD) is widely used to improve large language models' (LLMs) reasoning and test-time scaling.
    Approach: They propose a diversity-aware initialisation that selects a more diverse pool of candidate answers, increasing the likelihood that a correct hypothesis is present at the start of debate.
    Outcome: The proposed protocol outperforms vanilla MAD and majority vote on six reasoning-oriented QA benchmarks.

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