Factorize, Reconstruct, Enhance: A Unified Framework for Multimodal Sentiment Analysis
FUSE-Net is proposed, a Factorized and Unified Semantic Enhancement framework that decomposes each modality into shared, specific, and noise subspaces and applies contrastive learning, an information-gain constraint, and duality constraints for structured regularization to preserve task-relevant semantics during factorization.