38 citations · 40 across the 3 of their papers we have counts for
3 papers
cs.LG2023★ 38 cited
Graph Contrastive Learning with Generative Adversarial Network
Cheng Wu, Chaokun Wang, Jingcao Xu +5
Graph Neural Networks (GNNs) have demonstrated promising results on exploiting node representations for many downstream tasks through supervised end-to-end training. To deal with t…
cs.IR2023★ 2 cited
PANE-GNN: Unifying Positive and Negative Edges in Graph Neural Networks for Recommendation
Ziyang Liu, Chaokun Wang, Jingcao Xu +5
Recommender systems play a crucial role in addressing the issue of information overload by delivering personalized recommendations to users. In recent years, there has been a growi…
cs.IR2023
Instant Representation Learning for Recommendation over Large Dynamic Graphs
Cheng Wu, Chaokun Wang, Jingcao Xu +7
Recommender systems are able to learn user preferences based on user and item representations via their historical behaviors. To improve representation learning, recent recommendat…