ShapKO: Shapley-Adaptive Modality Knockout for Robust Multimodal Learning

arXiv:2607.09884v1 Announce Type: new Abstract: Multimodal medical models often degrade when inputs are missing, a common scenario in real-world clinical workflows. Separately, even when all modalities are present, modality dominance is observed during training, where optimization over-relies on a highly predictive modality and undertrains complementary sources, resulting in poor robustness under partial availability. While training-time modality knockout improves missing-modality robustness, ex...