Nowadays, graph collaborative filtering is widely used in recommender system as an important technique. In order to alleviate the common data sparsity problem in collaborative filtering, contrastive learning techniques have been utilized to assist ...

Generative sequential recommendations based on Large Language Models (LLMs) have garnered significant attention, due to the remarkable generalized capabilities of LLMs. However, the conventional ID-based representation not only widens the gap ...

The realm of recommender systems has experienced a notable upswing in interest, particularly in the context of multi-modality, where user preferences are characterized through the integration of behavioral data and diverse modal information ...