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This work proposes FourIer Representation Editor (FIRE), a novel multimodal TTA approach that directly edits semantically rich intermediate representations, and demonstrates the superiority of FIRE over existing multimodal TTA methods.
This paper proposes multimodal Max Confidence Regularization (MaxCR) to dynamically intervene in modality semantic confidence, and reveals that this flaw stems from unimodal characteristics rather than multimodal learning, and this confidence discrepancy can be corrected by positive cross-modal intervention.
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