Learning to Reason About Implicit Multimodal Harm: From Diagnosis to Generalization

arXiv:2605.29951v2 Announce Type: replace Abstract: A benign image paired with a benign caption can become harmful only in combination, making detection fundamentally a cross-modal reasoning problem. Existing multimodal harm benchmarks evaluate only classification accuracy, leaving unclear whether models identify the cross-modal mechanism that produces harm. We introduce MuPHI (Multimodal Pragmatic Harm Interpretation), a controlled diagnostic benchmark in which harm arises purely from image-text composition, with benign counterfactuals and annotated harm rationales. Using MuPHI, we systematic

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