Towards Fair Graph Anomaly Detection: Problem, Benchmark Datasets, and Evaluation
We address fairness issues in graph anomaly detection, providing benchmark datasets and comprehensive evaluation frameworks for fair anomaly detection on graphs....
Jul 4, 2024
CODER
Graph-based code recommendation framework for open source developers. Leverages heterogeneous OSS contribution networks (repositories, users, issues, pull requests) to deliver multi-modal recommendations. WebConf 2023 Oral.
Apr 30, 2023
Code Recommendation for Open Source Project Developers
CODER is a graph-based code recommendation framework for open source developers, modeling heterogeneous OSS contribution networks to deliver multi-modal recommendations across realistic workloads.
Apr 30, 2023
Reinforcement Subgraph Reasoning for Fake News Detection
A novel subgraph reasoning paradigm for fake news detection that provides explainability while improving generalization through reinforcement learning and hierarchical graph attention networks.
Jun 1, 2022
FinerFact
A fine-grained reasoning framework for fake news detection that mirrors the human information-processing model, using a prior-aware bi-channel kernel graph network over evidence types. AAAI 2022 Oral.
Feb 1, 2022
Towards Fine-Grained Reasoning for Fake News Detection
We propose a fine-grained reasoning framework for fake news detection by following the human information-processing model and designing a prior-aware bi-channel kernel graph network....
Jan 1, 2022