AI RESEARCH
Towards Robust Multimodal Physiological Foundation Models: Handling Arbitrary Missing Modalities
arXiv CS.LG
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ArXi:2504.19596v3 Announce Type: replace-cross Multimodal physiological signals, such as EEG, ECG, EOG, and EMG, are crucial for healthcare and brain-computer interfaces. While existing methods rely on specialized architectures and dataset-specific fusion strategies, they struggle to learn universal representations that generalize across datasets and handle missing modalities at inference time.