DiffMM

Researchers from HKU and Tencent proposed a new paradigm of multimodal recommendation system, DiffMM, which aims to improve the accuracy of short video recommendations. The system creates a graph containing user and video information and uses graph diffusion and contrastive learning techniques to better understand the relationship between users and videos, thereby achieving more accurate recommendations. The model method of DiffMM mainly consists of three parts: multimodal graph diffusion model, multimodal graph aggregation, and cross-modal contrast enhancement. Among them, the multimodal graph diffusion model combines user-item collaborative signals with multimodal...