Research map / Vision-language and multimodal / Multimodal LLMs
Toward Multimodal Fake News Detection by Multi-perspective Rationale Generation and Verification
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Proposes a multimodal fake news detection approach that generates and verifies multi-perspective rationales with MLLMs (abstract only available).
Problem
Detecting multimodal fake news, where deceptive text-image combinations on social media are hard for unimodal methods to handle.
Approach
Uses multimodal large language models to generate rationales from multiple perspectives and verifies them for fake news detection; the abstract is truncated so specifics are unknown.
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