839 citations · 1.4k across the 16 of their papers we have counts for
17 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…
Towards Robust Cross-Domain Recommendation with Joint Identifiability of User Preference
Jing Du, Zesheng Ye, Bin Guo +5
Recent cross-domain recommendation (CDR) studies assume that disentangled domain-shared and domain-specific user representations can mitigate domain gaps and facilitate effective k…
Learning To Sample the Meta-Paths for Social Event Detection
Congbo Ma, Hu Wang, Zitai Qiu +5
Social media data is inherently rich, as it includes not only text content, but also users, geolocation, entities, temporal information, and their relationships. This data richness…
Hy-DeFake: Hypergraph Neural Networks for Detecting Fake News in Online Social Networks
Xing Su, Jian Yang, Jia Wu +1
Nowadays social media is the primary platform for people to obtain news and share information. Combating online fake news has become an urgent task to reduce the damage it causes t…
Discriminative Graph-level Anomaly Detection via Dual-students-teacher Model
Fu Lin, Xuexiong Luo, Jia Wu +4
Different from the current node-level anomaly detection task, the goal of graph-level anomaly detection is to find abnormal graphs that significantly differ from others in a graph…
Heterogeneous Social Event Detection via Hyperbolic Graph Representations
Zitai Qiu, Jia Wu, Jian Yang +2
Social events reflect the dynamics of society and, here, natural disasters and emergencies receive significant attention. The timely detection of these events can provide organisat…
Mining User-aware Multi-relations for Fake News Detection in Large Scale Online Social Networks
Xing Su, Jian Yang, Jia Wu +1
Users' involvement in creating and propagating news is a vital aspect of fake news detection in online social networks. Intuitively, credible users are more likely to share trustwo…
State of the Art and Potentialities of Graph-level Learning
Zhenyu Yang, Ge Zhang, Jia Wu +9
Graphs have a superior ability to represent relational data, like chemical compounds, proteins, and social networks. Hence, graph-level learning, which takes a set of graphs as inp…
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…
Graph-level Neural Networks: Current Progress and Future Directions
Ge Zhang, Jia Wu, Jian Yang +6
Graph-structured data consisting of objects (i.e., nodes) and relationships among objects (i.e., edges) are ubiquitous. Graph-level learning is a matter of studying a collection of…
Knowledge-aware Document Summarization: A Survey of Knowledge, Embedding Methods and Architectures
Yutong Qu, Wei Emma Zhang, Jian Yang +2
Knowledge-aware methods have boosted a range of natural language processing applications over the last decades. With the gathered momentum, knowledge recently has been pumped into…
A Survey on Location-Driven Influence Maximization
Taotao Cai, Quan Z. Sheng, Xiangyu Song +5
Influence Maximization (IM), which aims to select a set of users from a social network to maximize the expected number of influenced users, is an evergreen hot research topic. Its…
dFDA-VeD: A Dynamic Future Demand Aware Vehicle Dispatching System
Yang Guo, Tarique Anwar, Jian Yang +1
With the rising demand of smart mobility, ride-hailing service is getting popular in the urban regions. These services maintain a system for serving the incoming trip requests by d…
A Comprehensive Survey on Graph Anomaly Detection with Deep Learning
Xiaoxiao Ma, Jia Wu, Shan Xue +5
Anomalies represent rare observations (e.g., data records or events) that deviate significantly from others. Over several decades, research on anomaly mining has received increasin…
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…