About Me

Hi! I am a third-year PhD student at the Hong Kong University of Science and Technology(Guangzhou). Previously, I received my master’s degree at Beijing University of Posts and Telecommunications, majoring at Cyberspace Security. I also received a bachelor degree in mathematics and applied mathematics from the same school. My research interests lie in the explanations of graph models and large language models (LLMs).

Publications

Towards the Explainability of Temporal Graph Networks via Memory Backtracking and Topological Attribution
^{Yazheng Liu, Xi Zhang, Sihong Xie, Hui Xiong
International Conference on Machine Learning (ICML), 2026, Spotlight(2.2%)}

Robust Explanations of Graph Neural Networks via Graph Curvatures
^{Yazheng Liu, Xi Zhang, Sihong Xie, Hui Xiong
Neural Information Processing Systems (NeurIPS), 2025}

Explanations of GNN on Evolving Graphs via Axiomatic Layer Edges
^{Yazheng Liu, Sihong Xie
International Conference on Learning Representations (ICLR), 2025}

A Differential Geometric View and Explainability of GNN on Evolving Graphs
^{Yazheng Liu, Xi Zhang, Sihong Xie
International Conference on Learning Representations (ICLR), 2023}

Trade less Accuracy for Fairness and Trade-off Explanation for GNN
^{Yazheng Liu, Xi Zhang, Sihong Xie
Second International Workshop on Data science for equality, inclusion and well-being challenges, Bigdata workshop, 2022}