Xinzhe Jiang

CAFU: Constrained Alignment and Filtered Uniformity for Denoising Recommendation

In recommender systems, recent advances highlight the critical role of alignment and uniformity (AU) in representation learning. Specifically, AU-based methods pull positive user-item pairs closer (alignment) and spread the overall representation distribution (uniformity), typically relying on obser