4 papers
Slow Thinking for Sequential Recommendation
Junjie Zhang, Beichen Zhang, Wenqi Sun +4
To develop effective sequential recommender systems, numerous methods have been proposed to model historical user behaviors. Despite the effectiveness, these methods share the same…
Tapping the Potential of Large Language Models as Recommender Systems: A Comprehensive Framework and Empirical Analysis
Lanling Xu, Junjie Zhang, Bingqian Li +4
Recently, Large Language Models~(LLMs) such as ChatGPT have showcased remarkable abilities in solving general tasks, demonstrating the potential for applications in recommender sys…
Enhancing Graph Contrastive Learning with Reliable and Informative Augmentation for Recommendation
Bowen Zheng, Junjie Zhang, Hongyu Lu +4
Graph neural network(GNN) has been a powerful approach in collaborative filtering(CF) due to its ability to model high-order user-item relationships. Recently, to alleviate the dat…
Curriculum-scheduled Knowledge Distillation from Multiple Pre-trained Teachers for Multi-domain Sequential Recommendation
Wenqi Sun, Ruobing Xie, Junjie Zhang +3
Pre-trained recommendation models (PRMs) have received increasing interest recently. However, their intrinsically heterogeneous model structure, huge model size and computation cos…