In recent years, neural architecture-based recommender systems have achieved
tremendous success, but they still fall short of expectation when dealing with highly sparse …

Deep learning-based recommender systems have achieved remarkable success in recent
years. However, these methods usually heavily rely on labeled data (ie, user-item …

Recent years witness the success of pre-trained models to alleviate the data sparsity
problem in recommender systems. However, existing pre-trained models for …