A two-level reference alignment framework uses complete-modality samples and prototype voting to reduce decision drift and improve robustness in multimodal sentiment analysis under missing modalities.
Learning modality-specific representations with self- supervised multi-task learning for multimodal sentiment analysis
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Controlling Decision Drift in Multimodal Sentiment Analysis with Missing Modalities
A two-level reference alignment framework uses complete-modality samples and prototype voting to reduce decision drift and improve robustness in multimodal sentiment analysis under missing modalities.