DyMo dynamically selects reliable recovered modalities at inference by using task loss as a proxy for task-relevant information, outperforming prior discard-or-impute methods on image datasets.
MICINet: Multi-level inter-class confusing information removal for reliable multimodal classification.arXiv preprint arXiv:2502.19674,
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Inference-Time Dynamic Modality Selection for Incomplete Multimodal Classification
DyMo dynamically selects reliable recovered modalities at inference by using task loss as a proxy for task-relevant information, outperforming prior discard-or-impute methods on image datasets.