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

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 this https URL.

Computation and Language (cs.CL)

arXiv:2604.19005 [cs.CL]

(or arXiv:2604.19005v3 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2604.19005 Focus to learn more arXiv-issued DOI via DataCite

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