5 papers
TED: Related Party Transaction guided Tax Evasion Detection on Heterogeneous Graph
Yiming Xu, Bin Shi, Bo Dong +3
Tax evasion causes severe losses of government revenues and disturbs the economic order of fair competition. To help alleviate this problem, the latest tax evasion detection soluti…
Mitigating Instance Entanglement in Instance-Dependent Partial Label Learning
Rui Zhao, Bin Shi, Kai Sun +1
Partial label learning is a prominent weakly supervised classification task, where each training instance is ambiguously labeled with a set of candidate labels. In real-world scena…
Feature Bank Enhancement for Distance-based Out-of-Distribution Detection
Yuhang Liu, Yuefei Wu, Bin Shi +1
Out-of-distribution (OOD) detection is critical to ensuring the reliability of deep learning applications and has attracted significant attention in recent years. A rich body of li…
Out-of-Distribution Generalization on Graphs via Progressive Inference
Yiming Xu, Bin Shi, Zhen Peng +3
The development and evaluation of graph neural networks (GNNs) generally follow the independent and identically distributed (i.i.d.) assumption. Yet this assumption is often untena…
Training a Label-Noise-Resistant GNN with Reduced Complexity
Rui Zhao, Bin Shi, Zhiming Liang +3
Graph Neural Networks (GNNs) have been widely employed for semi-supervised node classification tasks on graphs. However, the performance of GNNs is significantly affected by label…