Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debate

Catalog evidence and recorded chart appearances. Inclusion is not an endorsement.

Source snapshot imported 2026-10-20. This is not a live feed. Source and contributions.

Evidence and limits

Finding: Debate increased divergence relative to self-reflection on tested tasks, but gains required controlled interaction and model judges were not always fair across different agents.

Impact: Watch bounded disagreement and stopping rules. Reject the judge agent as neutral by default.

Boundary: Two benchmark families do not establish durable workflow value. Next: how should judge bias and debate cost be measured prospectively?

Flags: narrow tasks; judge bias and degeneration

Record State: Catalog review recorded; not a performance endorsement

What was reviewed: Structure and relevance screened; not a full evaluation

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Recorded chart appearances

  • 2026-10-13: position 66. Relevant to the recorded review topic (see source); Structure and relevance screened; not a full evaluation evidence
  • 2026-10-12: position 65. Relevant to the recorded review topic (see source); Structure and relevance screened; not a full evaluation evidence