350 citations · 545 across the 5 of their papers we have counts for
6 papers
Adversarial Attacks Against Automated Fact-Checking: A Survey
Fanzhen Liu, Alsharif Abuadbba, Kristen Moore +5
In an era where misinformation spreads freely, fact-checking (FC) plays a crucial role in verifying claims and promoting reliable information. While automated fact-checking (AFC) h…
Towards Faithful Class-level Self-explainability in Graph Neural Networks by Subgraph Dependencies
Fanzhen Liu, Xiaoxiao Ma, Jian Yang +6
Enhancing the interpretability of graph neural networks (GNNs) is crucial to ensure their safe and fair deployment. Recent work has introduced self-explainable GNNs that generate e…
GCFL: A Gradient Correction-based Federated Learning Framework for Privacy-preserving CPSS
Jiayi Wan, Xiang Zhu, Fanzhen Liu +2
Federated learning, as a distributed architecture, shows great promise for applications in Cyber-Physical-Social Systems (CPSS). In order to mitigate the privacy risks inherent in…
DAGAD: Data Augmentation for Graph Anomaly Detection
Fanzhen Liu, Xiaoxiao Ma, Jia Wu +7
Graph anomaly detection in this paper aims to distinguish abnormal nodes that behave differently from the benign ones accounting for the majority of graph-structured instances. Rec…
A Comprehensive Survey on Community Detection with Deep Learning
Xing Su, Shan Xue, Fanzhen Liu +9
A community reveals the features and connections of its members that are different from those in other communities in a network. Detecting communities is of great significance in n…
Deep Learning for Community Detection: Progress, Challenges and Opportunities
Fanzhen Liu, Shan Xue, Jia Wu +6
As communities represent similar opinions, similar functions, similar purposes, etc., community detection is an important and extremely useful tool in both scientific inquiry and d…