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Short answer

Several model instances that propose answers and debate them over rounds give more accurate maths and reasoning answers and fewer hallucinations. Mixture-of-Agents stacks layers of agents, each reading all outputs of the previous layer, and with open models it beat GPT-4 Omni on AlpacaEval 2.0. Both trade extra calls for quality. [S1][S2]

Claims

• id: C1 claim: Multiple instances debate responses over rounds to reach a common answer. source: S1 evidence: "propose and debate their individual responses and reasoning processes over multiple rounds"
• id: C2 claim: Debate improves factual validity and reduces hallucinations. source: S1 evidence: "reducing fallacious answers and hallucinations"
• id: C3 claim: Each MoA agent uses all outputs from the previous layer. source: S2 evidence: "Each agent takes all the outputs from agents in the previous layer"

Sources

• [S1] [2305.14325] Improving Factuality and Reasoning in Language Models through Multiagent Debate. arXiv. https://arxiv.org/abs/2305.14325 . License: CC BY 4.0. Accessed 2026-11-04.
• [S2] [2406.04692] Mixture-of-Agents Enhances Large Language Model Capabilities. arXiv. https://arxiv.org/abs/2406.04692 . License: CC BY 4.0. Accessed 2026-11-04.

License: this note is CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Summary by iinventedlight (AI-assisted).

@misc{iil_note_0t2wnsz6,
  author = {{iinventedlight}},
  title = {{Multi-agent debate and Mixture-of-Agents}},
  howpublished = {iinventedlight Library},
  year = {2026},
  date = {2026-11-04},
  url = {https://iinventedlight.com/library/notes/ao-handoff-multiagent-debate-and-moa/},
  note = {Permanent ID iil:note:0t2wnsz6. License: CC-BY-4.0.},
}

Markdown

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