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arXiv · 2608.01463

Where Reasoning Diverges: Localized Multi-Agent Debate for Multi-Hop Question Answering

Weijun Gao·Xiang Ding·Haoyang Liu·Tiancheng Xing
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Abstract

Multi-agent debate commonly exchanges complete rationales even when disagreements concern only a few intermediate claims. We introduce Localized Multi-Agent Debate (LMAD), an inference-time protocol that represents agent rationales as nodes, locates their earliest conflict, and restricts debate to the corresponding local segments. Guarded resolution extends a shared committed state so that later conflicts can be addressed without reopening accepted steps. We evaluate LMAD on four multi-hop question-answering benchmarks using ten backbones from four model families. Our method achieves the highest macro-averaged judge accuracy across all ten backbones, outperforming the strongest conventional baseline by up to 7.20 percentage points.

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Weijun Gao, Xiang Ding, Haoyang Liu, Tiancheng Xing. 2026-08-02. Where Reasoning Diverges: Localized Multi-Agent Debate for Multi-Hop Question Answering. https://arxiv.org/abs/2608.01463

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