1 citations · 1 across the 4 of their papers we have counts for
4 papers
TA-GGAD: Testing-time Adaptive Graph Model for Generalist Graph Anomaly Detection
Xiong Zhang, Hong Peng, Changlong Fu +3
A significant number of anomalous nodes in the real world, such as fake news, noncompliant users, malicious transactions, and malicious posts, severely compromises the health of th…
Bridging Granularity Gaps: Hierarchical Semantic Learning for Cross-domain Few-shot Segmentation
Sujun Sun, Haowen Gu, Cheng Xie +3
Cross-domain Few-shot Segmentation (CD-FSS) aims to segment novel classes from target domains that are not involved in training and have significantly different data distributions…
JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation
Ji Shi, Chengxun Xie, Zhonghao Li +2
The discovery of new molecules based on the original chemical molecule distributions is of great importance in medicine. The graph transformer, with its advantages of high performa…
NoiseHGNN: Synthesized Similarity Graph-Based Neural Network For Noised Heterogeneous Graph Representation Learning
Xiong Zhang, Cheng Xie, Haoran Duan +1
Real-world graph data environments intrinsically exist noise (e.g., link and structure errors) that inevitably disturb the effectiveness of graph representation and downstream lear…