What Improves Multimodal Misinformation Detection? Answers from a Large-Scale Empirical Study

The paper investigates how different multimodal design choices affect the performance of misinformation detection systems. Using over 3,375 experiments across three benchmark datasets and various pre‑trained vision and language models, the authors systematically compare design options and conduct robustness analyses. The study offers practical guidance on which choices improve detection, when they may fail silently, and which pipeline components most influence model behavior, addressing four key research questions.

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• multimodal
• benchmarks