36 citations · 115 across the 10 of their papers we have counts for
10 papers
Federated Graph Condensation with Information Bottleneck Principles
Bo Yan, Sihao He, Cheng Yang +3
Graph condensation (GC), which reduces the size of a large-scale graph by synthesizing a small-scale condensed graph as its substitution, has benefited various graph learning tasks…
Abnormal Event Detection via Hypergraph Contrastive Learning
Bo Yan, Cheng Yang, Chuan Shi +2
Abnormal event detection, which refers to mining unusual interactions among involved entities, plays an important role in many real applications. Previous works mostly over-simplif…
Graph Mining for Cybersecurity: A Survey
Bo Yan, Cheng Yang, Chuan Shi +4
The explosive growth of cyber attacks nowadays, such as malware, spam, and intrusions, caused severe consequences on society. Securing cyberspace has become an utmost concern for o…
MA-GCL: Model Augmentation Tricks for Graph Contrastive Learning
Xumeng Gong, Cheng Yang, Chuan Shi
Contrastive learning (CL), which can extract the information shared between different contrastive views, has become a popular paradigm for vision representation learning. Inspired…
Space4HGNN: A Novel, Modularized and Reproducible Platform to Evaluate Heterogeneous Graph Neural Network
Tianyu Zhao, Cheng Yang, Yibo Li +7
Heterogeneous Graph Neural Network (HGNN) has been successfully employed in various tasks, but we cannot accurately know the importance of different design dimensions of HGNNs due…
Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration
Xiao Wang, Hongrui Liu, Chuan Shi +1
Despite Graph Neural Networks (GNNs) have achieved remarkable accuracy, whether the results are trustworthy is still unexplored. Previous studies suggest that many modern neural ne…
From Symbols to Embeddings: A Tale of Two Representations in Computational Social Science
Huimin Chen, Cheng Yang, Xuanming Zhang +3
Computational Social Science (CSS), aiming at utilizing computational methods to address social science problems, is a recent emerging and fast-developing field. The study of CSS i…
Evaluating Modules in Graph Contrastive Learning
Ganqu Cui, Yufeng Du, Cheng Yang +5
The recent emergence of contrastive learning approaches facilitates the application on graph representation learning (GRL), introducing graph contrastive learning (GCL) into the li…
KACC: A Multi-task Benchmark for Knowledge Abstraction, Concretization and Completion
Jie Zhou, Shengding Hu, Xin Lv +6
A comprehensive knowledge graph (KG) contains an instance-level entity graph and an ontology-level concept graph. The two-view KG provides a testbed for models to "simulate" human'…
MixPoet: Diverse Poetry Generation via Learning Controllable Mixed Latent Space
Xiaoyuan Yi, Ruoyu Li, Cheng Yang +2
As an essential step towards computer creativity, automatic poetry generation has gained increasing attention these years. Though recent neural models make prominent progress in so…