Mian Ren

Interaction-Specific Diffusion Scheduling Guided by Temporal Priors for Sequential Recommendation

Sequential recommendation must infer evolving preferences from interaction histories that are sparse, temporally irregular, and heterogeneous in relevance. Existing diffusion-based recommenders improve representation generation and recovery, yet their perturbation strength is typically governed by the diffusion step an...