Yushun Dong

According to our database, Yushun Dong authored at least 64 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

A Systematic Survey of Model Extraction Attacks and Defenses: State-of-the-Art and Perspectives.

Kaixiang Zhao, Lincan Li, Kaize Ding, Neil Zhenqiang Gong, Yue Zhao, Yushun Dong

CoRR, August, 2025

DESIGN: Encrypted GNN Inference via Server-Side Input Graph Pruning.

Kaixiang Zhao, Joseph Yousry Attalla, Qian Lou, Yushun Dong

CoRR, July, 2025

A Survey on Model Extraction Attacks and Defenses for Large Language Models.

Kaixiang Zhao, Lincan Li, Kaize Ding, Neil Zhenqiang Gong, Yue Zhao, Yushun Dong

CoRR, June, 2025

Learning from the Storm: A Multivariate Machine Learning Approach to Predicting Hurricane-Induced Economic Losses.

Bolin Shen, Eren Erman Ozguven, Yue Zhao, Guang Wang, Yiqun Xie, Yushun Dong

CoRR, June, 2025

CEGA: A Cost-Effective Approach for Graph-Based Model Extraction and Acquisition.

Zebin Wang, Menghan Lin, Bolin Shen, Ken Anderson, Molei Liu, Tianxi Cai, Yushun Dong

CoRR, June, 2025

TyphoFormer: Language-Augmented Transformer for Accurate Typhoon Track Forecasting.

Lincan Li, Eren Erman Ozguven, Yue Zhao, Guang Wang, Yiqun Xie, Yushun Dong

CoRR, June, 2025

Tracing LLM Reasoning Processes with Strategic Games: A Framework for Planning, Revision, and Resource-Constrained Decision Making.

Xiaopeng Yuan, Xingjian Zhang, Ke Xu, Yifan Xu, Lijun Yu, Jindong Wang, Yushun Dong, Haohan Wang

CoRR, June, 2025

MISLEADER: Defending against Model Extraction with Ensembles of Distilled Models.

Xueqi Cheng, Minxing Zheng, Shixiang Zhu, Yushun Dong

CoRR, June, 2025

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs.

Zihan Chen, Xingbo Fu, Yushun Dong, Jundong Li, Cong Shen

CoRR, April, 2025

GLIP-OOD: Zero-Shot Graph OOD Detection with Foundation Model.

Haoyan Xu, Zhengtao Yao, Xuzhi Zhang, Ziyi Wang, Langzhou He, Yushun Dong, Philip S. Yu, Mengyuan Li, Yue Zhao

CoRR, April, 2025

Measuring Computational Universality of Fully Homomorphic Encryption.

Jiaqi Xue, Xin Xin, Wei Zhang, Mengxin Zheng, Qianqian Song, Minxuan Zhou, Yushun Dong, Dongjie Wang, Xun Chen, Jiafeng Xie, Liqiang Wang, David Mohaisen, Hongyi Wu, Qian Lou

CoRR, April, 2025

Few-Shot Graph Out-of-Distribution Detection with LLMs.

Haoyan Xu, Zhengtao Yao, Yushun Dong, Ziyi Wang, Ryan A. Rossi, Mengyuan Li, Yue Zhao

CoRR, March, 2025

ATOM: A Framework of Detecting Query-Based Model Extraction Attacks for Graph Neural Networks.

Zhan Cheng, Bolin Shen, Tianming Sha, Yuan Gao, Shibo Li, Yushun Dong

CoRR, March, 2025

Generative AI in Transportation Planning: A Survey.

Longchao Da, Tiejin Chen, Zhuoheng Li, Shreyas Bachiraju, Huaiyuan Yao, Li Li, Yushun Dong, Xiyang Hu, Zhengzhong Tu, Dongjie Wang, Yue Zhao, Xuanyu Zhou, Ram Pendyala, Benjamin Stabler, Yezhou Yang, Xuesong Zhou, Hua Wei

CoRR, March, 2025

ExPath: Towards Explaining Targeted Pathways for Biological Knowledge Bases.

Rikuto Kotoge, Ziwei Yang, Zheng Chen, Yushun Dong, Yasuko Matsubara, Jimeng Sun, Yasushi Sakurai

CoRR, February, 2025

A Survey of Model Extraction Attacks and Defenses in Distributed Computing Environments.

Kaixiang Zhao, Lincan Li, Kaize Ding, Neil Zhenqiang Gong, Yue Zhao, Yushun Dong

CoRR, February, 2025

Harnessing Large Language Models for Disaster Management: A Survey.

Zhenyu Lei, Yushun Dong, Weiyu Li, Rong Ding, Qi Wang, Jundong Li

CoRR, January, 2025

PyOD 2: A Python Library for Outlier Detection with LLM-powered Model Selection.

Sihan Chen, Zhuangzhuang Qian, Wingchun Siu, Xingcan Hu, Jiaqi Li, Shawn Li, Yuehan Qin, Tiankai Yang, Zhuo Xiao, Wanghao Ye, Yichi Zhang, Yushun Dong, Yue Zhao

Proceedings of the Companion Proceedings of the ACM on Web Conference 2025, 2025

CEB: Compositional Evaluation Benchmark for Fairness in Large Language Models.

Song Wang, Peng Wang, Tong Zhou, Yushun Dong, Zhen Tan, Jundong Li

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Graph Neural Networks Are More Than Filters: Revisiting and Benchmarking from A Spectral Perspective.

Yushun Dong, Patrick Soga, Yinhan He, Song Wang, Jundong Li

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Harnessing Large Language Models for Disaster Management: A Survey.

Zhenyu Lei, Yushun Dong, Weiyu Li, Rong Ding, Qi R. Wang, Jundong Li

Proceedings of the Findings of the Association for Computational Linguistics, 2025

BrainMAP: Learning Multiple Activation Pathways in Brain Networks.

Song Wang, Zhenyu Lei, Zhen Tan, Jiaqi Ding, Xinyu Zhao, Yushun Dong, Guorong Wu, Tianlong Chen, Chen Chen, Aiying Zhang, Jundong Li

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

ST-FiT: Inductive Spatial-Temporal Forecasting with Limited Training Data.

Zhenyu Lei, Yushun Dong, Jundong Li, Chen Chen

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024

Learning Hierarchical Task Structures for Few-shot Graph Classification.

Song Wang, Yushun Dong, Xiao Huang, Chen Chen, Jundong Li

ACM Trans. Knowl. Discov. Data, April, 2024

Federated Graph Learning with Graphless Clients.

Xingbo Fu, Song Wang, Yushun Dong, Binchi Zhang, Chen Chen, Jundong Li

Trans. Mach. Learn. Res., 2024

Political-LLM: Large Language Models in Political Science.

Lincan Li, Jiaqi Li, Catherine Chen, Fred Gui, Hongjia Yang, Chenxiao Yu, Zhengguang Wang, Jianing Cai, Junlong Aaron Zhou, Bolin Shen, Alex Qian, Weixin Chen, Zhongkai Xue, Lichao Sun, Lifang He, Hanjie Chen, Kaize Ding, Zijian Du, Fangzhou Mu, Jiaxin Pei, Jieyu Zhao, Swabha Swayamdipta, Willie Neiswanger, Hua Wei, Xiyang Hu, Shixiang Zhu, Tianlong Chen, Yingzhou Lu, Yang Shi, Lianhui Qin, Tianfan Fu, Zhengzhong Tu, Yuzhe Yang, Jaemin Yoo, Jiaheng Zhang, Ryan A. Rossi, Liang Zhan, Liang Zhao, Emilio Ferrara, Yan Liu, Furong Huang, Xiangliang Zhang, Lawrence Rothenberg, Shuiwang Ji, Philip S. Yu, Yue Zhao, Yushun Dong

CoRR, 2024

Explaining Graph Neural Networks with Large Language Models: A Counterfactual Perspective for Molecular Property Prediction.

Yinhan He, Zaiyi Zheng, Patrick Soga, Yaozhen Zhu, Yushun Dong, Jundong Li

CoRR, 2024

FredNormer: Frequency Domain Normalization for Non-stationary Time Series Forecasting.

Xihao Piao, Zheng Chen, Yushun Dong, Yasuko Matsubara, Yasushi Sakurai

CoRR, 2024

A Benchmark for Fairness-Aware Graph Learning.

Yushun Dong, Song Wang, Zhenyu Lei, Zaiyi Zheng, Jing Ma, Chen Chen, Jundong Li

CoRR, 2024

Safety in Graph Machine Learning: Threats and Safeguards.

Song Wang, Yushun Dong, Binchi Zhang, Zihan Chen, Xingbo Fu, Yinhan He, Cong Shen, Chuxu Zhang, Nitesh V. Chawla, Jundong Li

CoRR, 2024

PyGDebias: A Python Library for Debiasing in Graph Learning.

Yushun Dong, Zhenyu Lei, Zaiyi Zheng, Song Wang, Jing Ma, Alex Jing Huang, Chen Chen, Jundong Li

Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

SD-Attack: Targeted Spectral Attacks on Graphs.

Xianren Zhang, Jing Ma, Yushun Dong, Chen Chen, Min Gao, Jundong Li

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2024

Rethinking Fair Graph Neural Networks from Re-balancing.

Zhixun Li, Yushun Dong, Qiang Liu, Jeffrey Xu Yu

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

IDEA: A Flexible Framework of Certified Unlearning for Graph Neural Networks.

Yushun Dong, Binchi Zhang, Zhenyu Lei, Na Zou, Jundong Li

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Towards Certified Unlearning for Deep Neural Networks.

Binchi Zhang, Yushun Dong, Tianhao Wang, Jundong Li

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Adversarial Attacks on Fairness of Graph Neural Networks.

Binchi Zhang, Yushun Dong, Chen Chen, Yada Zhu, Minnan Luo, Jundong Li

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Explaining Graph Neural Networks with Large Language Models: A Counterfactual Perspective on Molecule Graphs.

Yinhan He, Zaiyi Zheng, Patrick Soga, Yaochen Zhu, Yushun Dong, Jundong Li

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

KG-CF: Knowledge Graph Completion with Context Filtering under the Guidance of Large Language Models.

Zaiyi Zheng, Yushun Dong, Song Wang, Haochen Liu, Qi Wang, Jundong Li

Proceedings of the IEEE International Conference on Big Data, 2024

Knowledge Graph-Enhanced Large Language Models via Path Selection.

Haochen Liu, Song Wang, Yaochen Zhu, Yushun Dong, Jundong Li

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

Fairness in Graph Mining: A Survey.

Yushun Dong, Jing Ma, Song Wang, Chen Chen, Jundong Li

IEEE Trans. Knowl. Data Eng., October, 2023

ELEGANT: Certified Defense on the Fairness of Graph Neural Networks.

Yushun Dong, Binchi Zhang, Hanghang Tong, Jundong Li

CoRR, 2023

Few-shot Node Classification with Extremely Weak Supervision.

Song Wang, Yushun Dong, Kaize Ding, Chen Chen, Jundong Li

Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

When Newer is Not Better: Does Deep Learning Really Benefit Recommendation From Implicit Feedback?

Yushun Dong, Jundong Li, Tobias Schnabel

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

RELIANT: Fair Knowledge Distillation for Graph Neural Networks.

Yushun Dong, Binchi Zhang, Yiling Yuan, Na Zou, Qi Wang, Jundong Li

Proceedings of the 2023 SIAM International Conference on Data Mining, 2023

Empower Post-hoc Graph Explanations with Information Bottleneck: A Pre-training and Fine-tuning Perspective.

Jihong Wang, Minnan Luo, Jundong Li, Yun Lin, Yushun Dong, Jin Song Dong, Qinghua Zheng

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Fairness in Graph Machine Learning: Recent Advances and Future Prospectives.

Yushun Dong, Oyku Deniz Kose, Yanning Shen, Jundong Li

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Spatial-Temporal Networks for Antibiogram Pattern Prediction.

Xingbo Fu, Chen Chen, Yushun Dong, Anil Vullikanti, Eili Y. Klein, Gregory Madden, Jundong Li

Proceedings of the 11th IEEE International Conference on Healthcare Informatics, 2023

GiGaMAE: Generalizable Graph Masked Autoencoder via Collaborative Latent Space Reconstruction.

Yucheng Shi, Yushun Dong, Qiaoyu Tan, Jundong Li, Ninghao Liu

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Interpreting Unfairness in Graph Neural Networks via Training Node Attribution.

Yushun Dong, Song Wang, Jing Ma, Ninghao Liu, Jundong Li

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Federated Graph Machine Learning: A Survey of Concepts, Techniques, and Applications.

Xingbo Fu, Binchi Zhang, Yushun Dong, Chen Chen, Jundong Li

SIGKDD Explor., 2022

Fairness in Graph Mining: A Survey.

Yushun Dong, Jing Ma, Chen Chen, Jundong Li

CoRR, 2022

Assessing the Causal Impact of COVID-19 Related Policies on Outbreak Dynamics: A Case Study in the US.

Jing Ma, Yushun Dong, Zheng Huang, Daniel Mietchen, Jundong Li

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks.

Yushun Dong, Ninghao Liu, Brian Jalaian, Jundong Li

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Empowering Next POI Recommendation with Multi-Relational Modeling.

Zheng Huang, Jing Ma, Yushun Dong, Natasha Zhang Foutz, Jundong Li

Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

Contrastive Attributed Network Anomaly Detection with Data Augmentation.

Zhiming Xu, Xiao Huang, Yue Zhao, Yushun Dong, Jundong Li

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2022

Improving Fairness in Graph Neural Networks via Mitigating Sensitive Attribute Leakage.

Yu Wang, Yuying Zhao, Yushun Dong, Huiyuan Chen, Jundong Li, Tyler Derr

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

GUIDE: Group Equality Informed Individual Fairness in Graph Neural Networks.

Weihao Song, Yushun Dong, Ninghao Liu, Jundong Li

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

On Structural Explanation of Bias in Graph Neural Networks.

Yushun Dong, Song Wang, Yu Wang, Tyler Derr, Jundong Li

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

FAITH: Few-Shot Graph Classification with Hierarchical Task Graphs.

Song Wang, Yushun Dong, Xiao Huang, Chen Chen, Jundong Li

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

2021

Graph Neural Networks with Adaptive Frequency Response Filter.

Yushun Dong, Kaize Ding, Brian Jalaian, Shuiwang Ji, Jundong Li

CoRR, 2021

Individual Fairness for Graph Neural Networks: A Ranking based Approach.

Yushun Dong, Jian Kang, Hanghang Tong, Jundong Li

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

AdaGNN: Graph Neural Networks with Adaptive Frequency Response Filter.

Yushun Dong, Kaize Ding, Brian Jalaian, Shuiwang Ji, Jundong Li

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2019

Learning Route Planning from Experienced Drivers Using Generalized Value Iteration Network.

Xiao Wang, Quan Yuan, Zhihan Liu, Yushun Dong, Xiaojuan Wei, Jinglin Li

Proceedings of the Internet of Vehicles. Technologies and Services Toward Smart Cities, 2019

Forecasting Pavement Performance with a Feature Fusion LSTM-BPNN Model.

Yushun Dong, Yingxia Shao, Xiaotong Li, Sili Li, Lei Quan, Wei Zhang, Junping Du

Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019