3 papers
cs.LG2025
Str-GCL: Structural Commonsense Driven Graph Contrastive Learning
Dongxiao He, Yongqi Huang, Jitao Zhao +2
Graph Contrastive Learning (GCL) is a widely adopted approach in self-supervised graph representation learning, applying contrastive objectives to produce effective representations…
cs.AI2025
Single-Node Trigger Backdoor Attacks in Graph-Based Recommendation Systems
Runze Li, Di Jin, Xiaobao Wang +3
Graph recommendation systems have been widely studied due to their ability to effectively capture the complex interactions between users and items. However, these systems also exhi…
cs.LG2025
Does GCL Need a Large Number of Negative Samples? Enhancing Graph Contrastive Learning with Effective and Efficient Negative Sampling
Yongqi Huang, Jitao Zhao, Dongxiao He +3
Graph Contrastive Learning (GCL) aims to self-supervised learn low-dimensional graph representations, primarily through instance discrimination, which involves manually mining posi…