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arXiv · 2604.19005

Debating the Unspoken: Role-Anchored Multi-Agent Reasoning for Half-Truth Detection

Yixuan Tang·Yirui Zhang·Hang Feng·Anthony K. H. Tung
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Abstract

Half-truths, claims that are factually correct yet misleading due to omitted context, remain a blind spot for fact verification systems focused on explicit falsehoods. Addressing such omission-based manipulation requires reasoning not only about what is said, but also about what is left unsaid. We propose RADAR, a role-anchored multi-agent debate framework for omission-aware fact verification under realistic, noisy retrieval. RADAR assigns complementary roles to a Politician and a Scientist, who reason adversarially over shared retrieved evidence, moderated by a neutral Judge. A dual-threshold early termination controller adaptively decides when sufficient reasoning has been reached to issue a verdict. Experiments show that RADAR consistently outperforms strong single- and multi-agent baselines across datasets and backbones, improving omission detection accuracy while reducing reasoning cost. These results demonstrate that role-anchored, retrieval-grounded debate with adaptive control is an effective and scalable framework for uncovering missing context in fact verification. The code is available at https://github.com/tangyixuan/RADAR.

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Yixuan Tang, Yirui Zhang, Hang Feng, Anthony K. H. Tung. 2026-04-21. Debating the Unspoken: Role-Anchored Multi-Agent Reasoning for Half-Truth Detection. https://arxiv.org/abs/2604.19005

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