Multimodal Claim Extraction for Fact-Checking

This work introduces the first benchmark for multimodal claim extraction from social media posts, essential for automated fact-checking. It evaluates state-of-the-art MLLMs and proposes MICE, an intent-aware framework, to address challenges in modeling rhetorical intent and contextual cues.