733 citations · 2.4k across the 107 of their papers we have counts for
14 papers · 1 filter
NIR-Prompt: A Multi-task Generalized Neural Information Retrieval Training Framework
Shicheng Xu, Liang Pang, Huawei Shen +1
Information retrieval aims to find information that meets users' needs from the corpus. Different needs correspond to different IR tasks such as document retrieval, open-domain que…
Towards Generalizable Graph Contrastive Learning: An Information Theory Perspective
Yige Yuan, Bingbing Xu, Huawei Shen +4
Graph contrastive learning (GCL) emerges as the most representative approach for graph representation learning, which leverages the principle of maximizing mutual information (Info…
Hierarchical Estimation for Effective and Efficient Sampling Graph Neural Network
Yang Li, Bingbing Xu, Qi Cao +2
Improving the scalability of GNNs is critical for large graphs. Existing methods leverage three sampling paradigms including node-wise, layer-wise and subgraph sampling, then desig…
DyTed: Disentangled Representation Learning for Discrete-time Dynamic Graph
Kaike Zhang, Qi Cao, Gaolin Fang +4
Unsupervised representation learning for dynamic graphs has attracted a lot of research attention in recent years. Compared with static graph, the dynamic graph is a comprehensive…
Adversarial for Social Privacy: A Poisoning Strategy to Degrade User Identity Linkage
Jiangli Shao, Yongqing Wang, Boshen Shi +3
Privacy issues on social networks have been extensively discussed in recent years. The user identity linkage (UIL) task, aiming at finding corresponding users across different soci…
Adversarial Camouflage for Node Injection Attack on Graphs
Shuchang Tao, Qi Cao, Huawei Shen +4
Node injection attacks on Graph Neural Networks (GNNs) have received increasing attention recently, due to their ability to degrade GNN performance with high attack success rates.…