79 citations · 117 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
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…
cs.IR2023★ 79 cited
Multi-behavior Self-supervised Learning for Recommendation
Jingcao Xu, Chaokun Wang, Cheng Wu +6
Modern recommender systems often deal with a variety of user interactions, e.g., click, forward, purchase, etc., which requires the underlying recommender engines to fully understa…