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Semantic features derived from Visual Question Answering can dramatically enhance the robustness of cancer prognosis models across diverse clinical settings.
EEG foundation models struggle with limited data because of structural mismatch, but SCOPE solves this by creating structured prototypes that guide adaptation, leading to better generalization.
