Sentiment-Intensity-Aware Contrastive Learning with Hierarchical Information Bottleneck for Multimodal Sentiment Analysis
In multimodal sentiment analysis, textual, acoustic, and visual modalities often contain redundant and noisy information. Such information increases model complexity and weakens core sentiment representations, degrading accuracy and robustness. To address this issue, we propose CLIBN, a multimodal sentiment recognition...