Adaptive Item-based Collaborative Structures via Noise Rescheduling in Diffusion for Generative Recommendation
Discrete Diffusion Models (DDMs) have recently been introduced to recommendation systems, modeling user history as a token generation process via iterative denoising. However, while effective at capturing user-level sequential patterns, these methods often fail to explicitly integrate item-based collaborative filtering...