Chenglei Huang

Capturing Dynamic User Interests Under Modality Imbalance for Multimodal Sequential Recommendation

Multimodal sequential recommender systems leverage diverse modal inputs to enhance the accuracy and relevance of personalized recommendations. However, existing fusion strategies often struggle to capture intricate cross-modal interactions, especially under the evolving dynamics of user intent. More