Trustworthy Multimodal Fusion for Robust Sentiment Analysis with Ordinal Constraints

A trustworthy multimodal sentiment analysis model that dynamically estimates uncertainty distributions for each modality and fuses them using Bayesian fusion to obtain a more robust multimodal representation. An ordinal regression loss is introduced to constrain the multimodal distributions to follow the ordinal relationships of sentiment categories.