3 accepted papers
Current multimodal sentiment analysis (MSA) and emotion recognition in conversations (ERC) methods based on pre-trained language models exhibit two primary limitations: 1) Once trained for MSA and ERC tasks, these pre-trained language models lose their original generalized capabilities. 2) They dema…
Most existing Multimodal Sentiment Analysis (MSA) models that are enhanced with external sentiment knowledge primarily focus on integrating this knowledge during the multimodal fusion stage, while overlooking its potential benefits during the multimodal representation learning process. In this study…
Recently, contrastive learning has begun to gain popularity in multimodal sentiment analysis (MSA). However, most of existing MSA methods based on contrastive learning lacks more detailed learning of the distribution of sample pairs with different sentiment intensity differences in the contrastive l…