Imbalanced multimodal learning that prioritizes the performance-dominant modality via unimodal ranking and asymmetric gradient modulation outperforms balanced approaches.
mmformer: Multimodal medical transformer for incomplete multimodal learning of brain tumor segmentation
2 Pith papers cite this work. Polarity classification is still indexing.
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LongMoE is a multimodal framework combining context-aware imputation, frequency-domain attentional tokenization, trajectory encoding, and context-conditioned sparse MoE routing to jointly handle modality missingness and longitudinal disease dynamics.
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PDMP: Rethinking Balanced Multimodal Learning via Performance-Dominant Modality Prioritization
Imbalanced multimodal learning that prioritizes the performance-dominant modality via unimodal ranking and asymmetric gradient modulation outperforms balanced approaches.
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LongMoE: Longitudinal Multimodal Learning via Trajectory-Aware Mixture-of-Experts
LongMoE is a multimodal framework combining context-aware imputation, frequency-domain attentional tokenization, trajectory encoding, and context-conditioned sparse MoE routing to jointly handle modality missingness and longitudinal disease dynamics.