Work

SA-GGCoT: social-aware graph-grounded chain-of-thought for multimodal claim verification under bounded evidence

Year: 2026

Type: article

Abstract: Multimodal misinformation often reuses authentic images while shifting key contextual details such as time, location, identity, or event description, making verification harder than ordinary image-text matching. We study this problem under a bounded-evidence setting, where verification relies on limited external evidence and, when available, early social traces collected within a fixed post-publication window. We propose SA-GGCoT, a three-stage framework that uses checkpoint-aware state tracking to localize conflicting evidence, LLMs to convert selected evidence into structured rationales, and a heterogeneous evidence graph to verify evidence consistency. Experiments on Weibo, PHEME, and MR $$^2$$ show consistent gains over protocol-matched baselines, with ablation and grounding analyses supporting the contribution of each component.

Source: Journal of King Saud University - Computer and Information Sciences

DOI: 10.1007/s44443-026-01072-z