Yushun Dong

Yushun Dong

Assistant Professor @FSU

Publications

Tutorials

  1. Fairness in Graph Machine Learning: Recent Advances and Future Prospectives [PDF] [Code] [Slides][Website]
    Yushun Dong, Oyku Deniz Kose, Yanning Shen, Jundong Li
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023).

  2. Fairness in Graph Mining: Metrics, Algorithms, and Applications [PDF] [Code] [Slides][Website]
    Yushun Dong, Jing Ma, Chen Chen, Jundong Li
    The IEEE International Conference on Data Mining (ICDM 2022).

Journal Publications

  1. Federated Graph Learning with Graphless Clients [PDF] [Code] [Slides]
    Xingbo Fu, Song Wang, Yushun Dong, Binchi Zhang, Chen Chen, Jundong Li
    Transactions on Machine Learning Research (TMLR) 2024.

  2. Learning Hierarchical Task Structures for Few-shot Graph Classification [PDF] [Code] [Slides]
    Song Wang, Yushun Dong, Xiao Huang, Chen Chen, Jundong Li
    IEEE Transactions on Knowledge Discovery from Data (TKDD) 2024.

  3. Fairness in Graph Mining: A Survey [PDF] [Code] [Slides]
    Yushun Dong, Jing Ma, Song Wang, Chen Chen, Jundong Li
    IEEE Transactions on Knowledge and Data Engineering (TKDE) 2023.

  4. Federated Graph Machine Learning: A Survey of Concepts, Techniques, and Applications [PDF] [Code] [Slides]
    Xingbo Fu, Binchi Zhang, Yushun Dong, Chen Chen, Jundong Li
    SIGKDD Explorations 2022.

Conference Publications

2024

  1. Adversarial Attacks on Fairness of Graph Neural Networks [PDF] [Code] [Slides]
    Binchi Zhang, Yushun Dong, Chen Chen, Yada Zhu, Minnan Luo, Jundong Li
    International Conference on Learning Representations (ICLR 2024).

  2. SD-Attack: Targeted Spectral Attacks on Graphs [PDF] [Code] [Slides]
    Xianren Zhang, Jing Ma, Yushun Dong, Chen Chen, Min Gao, Jundong Li
    Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2024).

  3. PyGDebias: A Python Library for Debiasing in Graph Learning [PDF] [Code] [Slides]
    Yushun Dong, Zhenyu Lei, Zaiyi Zheng, Song Wang, Jing Ma, Alex Jing Huang, Chen Chen, Jundong Li
    International Conference on World Wide Web (WWW 2024).

  4. Towards Certified Unlearning for Deep Neural Networks [PDF] [Code] [Slides]
    Binchi Zhang, Yushun Dong, Tianhao Wang, Jundong Li
    International Conference on Machine Learning (ICML 2024).

  5. Knowledge Graph-Enhanced Large Language Models via Path Selection [PDF] [Code] [Slides]
    Haochen Liu, Song Wang, Yaochen Zhu, Yushun Dong, Jundong Li
    Annual Meeting of the Association for Computational Linguistics Findings (ACL 2024).

  6. IDEA: A Flexible Framework of Certified Unlearning for Graph Neural Networks [PDF] [Code] [Slides]
    Yushun Dong, Binchi Zhang, Zhenyu Lei, Na Zou, Jundong Li
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024).

  7. Rethinking Fair Graph Neural Networks from Re-balancing [PDF] [Code] [Slides]
    Zhixun Li, Yushun Dong, Qiang Liu, Jeffrey Xu Yu
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024).

  8. Explaining Graph Neural Networks with Large Language Models: A Counterfactual Perspective on Molecule Graphs [PDF] [Code] [Slides]
    Yinhan He, Zaiyi Zheng, Patrick Soga, Yaochen Zhu, Yushun Dong, Jundong Li
    Empirical Methods in Natural Language Processing (EMNLP 2024).

  9. On Demonstration Selection for Improving Fairness in Language Models [PDF] [Code] [Slides]
    Song Wang, Peng Wang, Yushun Dong, Tong Zhou, Lu Cheng, Yangfeng Ji, Jundong Li
    Annual Conference on Neural Information Processing Systems, SoLaR Workshop (NeurIPS 2024).

  10. CEB: Compositional Evaluation Benchmark for Fairness in Large Language Models [PDF] [Code] [Slides]
    Song Wang, Peng Wang, Tong Zhou, Yushun Dong, Zhen Tan, Jundong Li
    Annual Conference on Neural Information Processing Systems, SoLaR Workshop (NeurIPS 2024).

  11. KG-CF: Knowledge Graph Completion with Context Filtering under the Guidance of Large Language Models [PDF] [Code] [Slides]
    Zaiyi Zheng, Yushun Dong, Song Wang, Haochen Liu, Qi Wang, Jundong Li
    IEEE International Conference on Big Data (BigData 2024).

2023

  1. GiGaMAE: Generalizable Graph Masked Autoencoder via Collaborative Latent Space Reconstruction [PDF] [Code] [Slides]
    Yucheng Shi, Yushun Dong, Qiaoyu Tan, Jundong Li, Ninghao Liu
    The Conference on Information and Knowledge Management (CIKM 2023).

  2. Empower Post-hoc Graph Explanations with Information Bottleneck: A Pre-training and Fine-tuning Perspective [PDF] [Code] [Slides]
    Jihong Wang, Minnan Luo, Jundong Li, Yun Lin, Yushun Dong, Jin Song Dong, Qinghua Zheng
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023).

  3. Post Disaster Private Well Water Contamination with Geosocial Network: A Case Study of Post Hurricane Harvey [PDF] [Code] [Slides]
    Rong Ding, Yushun Dong, Daniel Aldrich, Jundong Li, Kelsey Pieper, Qi Wang
    ASCE International Conference on Computing in Civil Engineering (i3CE 2023).

  4. When Newer is Not Better: Does Deep Learning Really Benefit Recommendation From Implicit Feedback? [PDF] [Code] [Slides]
    Yushun Dong, Jundong Li, Tobias Schnabel
    SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2023).

  5. RELIANT: Fair Knowledge Distillation for Graph Neural Networks [PDF] [Code] [Slides]
    Yushun Dong, Binchi Zhang, Yiling Yuan, Na Zou, Qi Wang, Jundong Li
    SIAM International Conference on Data Mining (SDM 2023).

  6. Interpreting Unfairness in Graph Neural Networks via Training Node Attribution [PDF] [Code] [Slides]
    Yushun Dong, Song Wang, Jing Ma, Ninghao Liu, Jundong Li
    AAAI Conference on Artificial Intelligence (AAAI 2023).

  7. Few-shot Node Classification with Extremely Weak Supervision [PDF] [Code] [Slides]
    Song Wang, Yushun Dong, Kaize Ding, Chen Chen, Jundong Li
    International Conference on Web Search and Data Mining (WSDM 2023).

  8. Spatial-Temporal Networks for Antibiogram Pattern Prediction [PDF] [Code] [Slides]
    Xingbo Fu, Chen Chen, Yushun Dong, Anil Vullikanti, Eili Klein, Gregory Madden and Jundong Li
    IEEE International Conference on Healthcare Informatics (ICHI 2023).

2022

  1. Federated Graph Machine Learning: A Survey of Concepts, Techniques, and Applications (Spotlight) [PDF] [Code] [Slides]
    Xingbo Fu, Binchi Zhang, Yushun Dong, Chen Chen, Jundong Li
    International Workshop on Federated Learning with Graph Data (FedGraph 2022).

  2. On Structural Explanation of Bias in Graph Neural Networks [PDF] [Code] [Slides]
    Yushun Dong, Song Wang, Yu Wang, Tyler Derr, Jundong Li
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022).

  3. GUIDE: Group Equality Informed Individual Fairness in Graph Neural Networks [PDF] [Code] [Slides]
    Weihao Song, Yushun Dong, Ninghao Liu, Jundong Li
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022).

  4. Fair View Graph Neural Network for Fair Node Representation Learning [PDF] [Code] [Slides]
    Yu Wang, Yuying Zhao, Yushun Dong, Huiyuan Chen, Jundong Li, Tyler Derr
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022).

  5. FAITH: Few-Shot Graph Classification with Hierarchical Task Graphs [PDF] [Code] [Slides]
    Song Wang, Yushun Dong, Xiao Huang, Chen Chen, Jundong Li
    International Joint Conference on Artificial Intelligence (IJCAI 2022).

  6. Empowering Next POI Recommendation with Multi-Relation Modeling (short paper) [PDF] [Code] [Slides]
    Zheng Huang, Jing Ma, Yushun Dong, Natasha Zhang Foutz, Jundong Li
    Special Interest Group on Information Retrieval (SIGIR 2022).

  7. EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks [PDF] [Code] [Slides]
    Yushun Dong, Ninghao Liu, Brian Jalaian, Jundong Li
    International Conference on World Wide Web (WWW 2022).

  8. Assessing the Causal Impact of COVID-19 Related Policies on Outbreak Dynamics: A Case Study in the US [PDF] [Code] [Slides]
    Jing Ma, Yushun Dong, Zheng Huang, Daniel Mietchen, Jundong Li
    International Conference on World Wide Web (WWW 2022).

  9. Contrastive Attributed Network Anomaly Detection with Data Augmentation [PDF] [Code] [Slides]
    Zhiming Xu, Xiao Huang, Yue Zhao, Yushun Dong, Jundong Li
    International Conference on Information and Knowledge Management (PAKDD 2022).

2021

  1. Graph Neural Networks with Adaptive Frequency Response Filter [PDF] [Code] [Slides]
    Yushun Dong, Kaize Ding, Brian Jalaian, Shuiwang Ji, Jundong Li
    International Conference on Information and Knowledge Management (CIKM 2021).

  2. Individual Fairness for Graph Neural Networks: A Ranking based Approach [PDF] [Code] [Slides]
    Yushun Dong, Jian Kang, Hanghang Tong, Jundong Li
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2021).

Earlier

  1. Forecasting Pavement Performance with a Feature Fusion LSTM-BPNN Model [PDF] [Code] [Slides]
    Yushun Dong, Yingxia Shao, Xiaotong Li, Sili Li, Lei Quan, Wei Zhang, Junping Du
    International Conference on Information and Knowledge Management (CIKM 2019).

  2. Learning Route Planning from Experienced Drivers Using Generalized Value Iteration Network [PDF] [Code] [Slides]
    Xiao Wang, Quan Yuan, Zhihan Liu, Yushun Dong, Xiaojuan Wei, Jinglin Li
    International Conference on Internet of Vehicles (IOV 2019).