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.

Computation and Language (cs.CL)

arXiv:2604.19005 [cs.CL]

(or arXiv:2604.19005v2 [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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