Publications

Preprints

1. LLM and GNN are Complementary: Distilling LLM for Multimodal Graph Learning
   Junjie Xu, Zongyu Wu, Minhua Lin, Xiang Zhang, Suhang Wang
   [Paper]

2. LanP: Rethinking the Impact of Language Priors in Large Vision-Language Models
   Zongyu Wu, Yuwei Niu, Hongcheng Gao, Minhua Lin, Zhiwei Zhang, Zhifang Zhang, Qi Shi, Yilong Wang, Sike Fu, Junjie Xu, Junjie Ao, Enyan Dai, Lei Feng, Xiang Zhang, Suhang Wang
   [Paper]

3. Let’s Grow an Unbiased Community: Guiding the Fairness of Graphs via New Links
   Jiahua Lu, Huaxiao Liu, Shuotong Bai, Junjie Xu, Renqiang Luo, Enyan Dai
   [Paper]

4. Self-Explainable Graph Neural Networks for Link Prediction
   Huaisheng Zhu, Dongsheng Luo, Xianfeng Tang, Junjie Xu, Hui Liu, Suhang Wang
   [Paper]

Conference Paper

1. DualEquiNet: A Dual-Space Hierarchical Equivariant Network for Large Biomolecules
   Junjie Xu, Jiahao Zhang, Mangal Prakash, Xiang Zhang, Suhang Wang
   (NeurIPS 2025) [Paper] [Code]

2. Geometric Hyena Networks for Large-scale Equivariant Learning
   Artem Moskalev, Mangal Prakash, Junjie Xu, Tianyu Cui, Rui Liao, Tommaso Mansi
   (ICML 2025) [Paper]

3. Beyond Sequence: Impact of Geometric Context for RNA Property Prediction
   Junjie Xu, Artem Moskalev, Tommaso Mansi, Mangal Prakash, Rui Liao
   (ICLR 2025) [Paper] [Code]
   (AIDrugX @ NeurIPS 2024) and (AI for New Drug Modalities @ NeurIPS 2024) [Paper]

4. Robustness-Inspired Defense Against Backdoor Attacks on Graph Neural Network
   Zhiwei Zhang, Minhua Lin, Junjie Xu, Zongyu Wu, Enyan Dai, Suhang Wang
   (ICLR 2025) [Paper]

5. HARMONY: A Multi-Representation Framework for RNA Property Prediction
   Junjie Xu, Artem Moskalev, Tommaso Mansi, Mangal Prakash, Rui Liao
   (AI4NA @ ICLR 2025) [Paper] [Code]

6. Stealing Training Graphs from Graph Neural Networks
   Minhua Lin, Enyan Dai, Junjie Xu, Jinyuan Jia, Xiang Zhang, Suhang Wang
   (KDD 2025) [Paper]

7. Shape-aware Graph Spectral Learning
   Junjie Xu, Enyan Dai, Dongsheng Luo, Xiang Zhang, Suhang Wang
   (CIKM 2024) [Paper] [Code]

8. HC-GST: Heterophily-aware Distribution Consistency-based Graph Self-training
   Fali Wang, Tianxiang Zhao, Junjie Xu, Suhang Wang
   (CIKM 2024) [Paper]

9. Enhancing GNNs with Limited Labeled Data by Actively Distilling Knowledge from LLMs
   Quan Li, Tianxiang Zhao, Lingwei Chen, Junjie Xu, and Suhang Wang
   (BigData 2024) [Paper]

10. HP-GMN: Graph Memory Networks for Heterophilous Graphs
    Junjie Xu, Enyan Dai, Xiang Zhang, Suhang Wang
    (ICDM 2022) [Paper] [Code]

11. Revisiting Time Series Outlier Detection: Definitions and Benchmarks
    Kwei-Herng Lai, Daochen Zha, Junjie Xu, Yue Zhao, Guanchu Wang, Xia Hu
    (NeurIPS 2021) Datasets and Benchmarks Track [Paper] [Code]

12. TODS: An Automated Time Series Outlier Detection System
    Kwei-Herng Lai, Daochen Zha, Guanchu Wang, Junjie Xu, Yue Zhao, Devesh Kumar, Yile Chen, Purav Zumkhawaka, Mingyang Wan, Diego Martinez, Xia Hu
    (AAAI 2021) demo track [Paper] [Code]

Journal Paper

1. A Comprehensive Survey of Small Language Models in the Era of Large Language Models: Techniques, Enhancements, Applications, Collaboration with LLMs, and Trustworthiness
   Fali Wang, Zhiwei Zhang, Xianren Zhang, Zongyu Wu, Tzuhao Mo, Qiuhao Lu, Wanjing Wang, Rui Li, Junjie Xu, Xianfeng Tang, Qi He, Yao Ma, Ming Huang, Suhang Wang
   (TIST) Transactions on Intelligent Systems and Technology [Paper] [Repo]

2. A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability
   Enyan Dai, Tianxiang Zhao, Huaisheng Zhu, Junjie Xu, Zhimeng Guo, Hui Liu, Jiliang Tang, Suhang Wang
   Machine Intelligence Research [Paper]