2 papers
cs.AI2026
Can LLMs Fool Graph Learning? Exploring Universal Adversarial Attacks on Text-Attributed Graphs
Zihui Chen, Yuling Wang, Pengfei Jiao +4
Text-attributed graphs (TAGs) enhance graph learning by integrating rich textual semantics and topological context for each node. While boosting expressiveness, they also expose ne…
cs.AI2025
HeTa: Relation-wise Heterogeneous Graph Foundation Attack Model
Yuling Wang, Zihui Chen, Pengfei Jiao +1
Heterogeneous Graph Neural Networks (HGNNs) are vulnerable, highlighting the need for tailored attacks to assess their robustness and ensure security. However, existing HGNN attack…