Forecasting Pavement Performance with a Feature Fusion LSTM-BPNN Model. - Yushun Dong; Yingxia Shao; Xiaotong Li; Sili Li; Lei Quan; Wei Zhang 056; Junping Du 001 (CIKM, 2019)

Learning Route Planning from Experienced Drivers Using Generalized Value Iteration Network. - Xiao Wang 002; Quan Yuan 004; Zhihan Liu; Yushun Dong; Xiaojuan Wei; Jinglin Li (IOV, 2019)

AdaGNN: Graph Neural Networks with Adaptive Frequency Response Filter. - Yushun Dong; Kaize Ding; Brian Jalaian; Shuiwang Ji; Jundong Li (CIKM, 2021)

Individual Fairness for Graph Neural Networks: A Ranking based Approach. - Yushun Dong; Jian Kang 008; Hanghang Tong; Jundong Li (KDD, 2021)

Graph Neural Networks with Adaptive Frequency Response Filter. - Yushun Dong; Kaize Ding; Brian Jalaian; Shuiwang Ji; Jundong Li (CoRR, 2021)

FAITH: Few-Shot Graph Classification with Hierarchical Task Graphs. - Song Wang 013; Yushun Dong; Xiao Huang 001; Chen Chen 022; Jundong Li (IJCAI, 2022)

On Structural Explanation of Bias in Graph Neural Networks. - Yushun Dong; Song Wang 013; Yu Wang 160; Tyler Derr; Jundong Li (KDD, 2022)

GUIDE: Group Equality Informed Individual Fairness in Graph Neural Networks. - Weihao Song; Yushun Dong; Ninghao Liu; Jundong Li (KDD, 2022)

Improving Fairness in Graph Neural Networks via Mitigating Sensitive Attribute Leakage. - Yu Wang 160; Yuying Zhao; Yushun Dong; Huiyuan Chen; Jundong Li; Tyler Derr (KDD, 2022)

Contrastive Attributed Network Anomaly Detection with Data Augmentation. - Zhiming Xu; Xiao Huang 001; Yue Zhao 016; Yushun Dong; Jundong Li (PAKDD (2), 2022)

Empowering Next POI Recommendation with Multi-Relational Modeling. - Zheng Huang; Jing Ma 002; Yushun Dong; Natasha Zhang Foutz; Jundong Li (SIGIR, 2022)

EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks. - Yushun Dong; Ninghao Liu; Brian Jalaian; Jundong Li (WWW, 2022)

Assessing the Causal Impact of COVID-19 Related Policies on Outbreak Dynamics: A Case Study in the US. - Jing Ma 002; Yushun Dong; Zheng Huang; Daniel Mietchen; Jundong Li (WWW, 2022)

Fairness in Graph Mining: A Survey. - Yushun Dong; Jing Ma 002; Chen Chen 022; Jundong Li (CoRR, 2022)

Federated Graph Machine Learning: A Survey of Concepts, Techniques, and Applications. - Xingbo Fu; Binchi Zhang; Yushun Dong; Chen Chen 022; Jundong Li (SIGKDD Explor., 2022)

Interpreting Unfairness in Graph Neural Networks via Training Node Attribution. - Yushun Dong; Song Wang 013; Jing Ma 002; Ninghao Liu; Jundong Li (AAAI, 2023)

GiGaMAE: Generalizable Graph Masked Autoencoder via Collaborative Latent Space Reconstruction. - Yucheng Shi; Yushun Dong; Qiaoyu Tan; Jundong Li; Ninghao Liu (CIKM, 2023)

Spatial-Temporal Networks for Antibiogram Pattern Prediction. - Xingbo Fu; Chen Chen 022; Yushun Dong; Anil Vullikanti; Eili Y. Klein; Gregory Madden; Jundong Li (ICHI, 2023)

Fairness in Graph Machine Learning: Recent Advances and Future Prospectives. - Yushun Dong; Oyku Deniz Kose; Yanning Shen; Jundong Li (KDD, 2023)

Empower Post-hoc Graph Explanations with Information Bottleneck: A Pre-training and Fine-tuning Perspective. - Jihong Wang 003; Minnan Luo; Jundong Li; Yun Lin 001; Yushun Dong; Jin Song Dong 001; Qinghua Zheng (KDD, 2023)

RELIANT: Fair Knowledge Distillation for Graph Neural Networks. - Yushun Dong; Binchi Zhang; Yiling Yuan; Na Zou 001; Qi Wang; Jundong Li (SDM, 2023)

When Newer is Not Better: Does Deep Learning Really Benefit Recommendation From Implicit Feedback? - Yushun Dong; Jundong Li; Tobias Schnabel (SIGIR, 2023)

Few-shot Node Classification with Extremely Weak Supervision. - Song Wang 013; Yushun Dong; Kaize Ding; Chen Chen 022; Jundong Li (WSDM, 2023)

ELEGANT: Certified Defense on the Fairness of Graph Neural Networks. - Yushun Dong; Binchi Zhang; Hanghang Tong; Jundong Li (CoRR, 2023)

Fairness in Graph Mining: A Survey. - Yushun Dong; Jing Ma 002; Song Wang 013; Chen Chen 022; Jundong Li (IEEE Trans. Knowl. Data Eng., 2023)

Knowledge Graph-Enhanced Large Language Models via Path Selection. - Haochen Liu; Song Wang 013; Yaochen Zhu; Yushun Dong; Jundong Li (ACL (Findings), 2024)

KG-CF: Knowledge Graph Completion with Context Filtering under the Guidance of Large Language Models. - Zaiyi Zheng; Yushun Dong; Song Wang 013; Haochen Liu; Qi Wang; Jundong Li (IEEE Big Data, 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 (EMNLP (Findings), 2024)

Adversarial Attacks on Fairness of Graph Neural Networks. - Binchi Zhang; Yushun Dong; Chen Chen 022; Yada Zhu; Minnan Luo; Jundong Li (ICLR, 2024)

Towards Certified Unlearning for Deep Neural Networks. - Binchi Zhang; Yushun Dong; Tianhao Wang; Jundong Li (ICML, 2024)

IDEA: A Flexible Framework of Certified Unlearning for Graph Neural Networks. - Yushun Dong; Binchi Zhang; Zhenyu Lei 004; Na Zou 001; Jundong Li (KDD, 2024)

Rethinking Fair Graph Neural Networks from Re-balancing. - Zhixun Li; Yushun Dong; Qiang Liu 006; Jeffrey Xu Yu (KDD, 2024)

SD-Attack: Targeted Spectral Attacks on Graphs. - Xianren Zhang; Jing Ma 002; Yushun Dong; Chen Chen 022; Min Gao 001; Jundong Li (PAKDD (2), 2024)

PyGDebias: A Python Library for Debiasing in Graph Learning. - Yushun Dong; Zhenyu Lei 004; Zaiyi Zheng; Song Wang 013; Jing Ma 002; Alex Jing Huang; Chen Chen 022; Jundong Li (WWW (Companion Volume), 2024)

Safety in Graph Machine Learning: Threats and Safeguards. - Song Wang 013; Yushun Dong; Binchi Zhang; Zihan Chen 002; Xingbo Fu; Yinhan He; Cong Shen 001; Chuxu Zhang; Nitesh V. Chawla; Jundong Li (CoRR, 2024)

A Benchmark for Fairness-Aware Graph Learning. - Yushun Dong; Song Wang 013; Zhenyu Lei 004; Zaiyi Zheng; Jing Ma 002; Chen Chen 022; Jundong Li (CoRR, 2024)

FredNormer: Frequency Domain Normalization for Non-stationary Time Series Forecasting. - Xihao Piao; Zheng Chen 012; Yushun Dong; Yasuko Matsubara; Yasushi Sakurai (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)

Political-LLM: Large Language Models in Political Science. - Lincan Li; Jiaqi Li; Catherine Chen 003; Fred Gui; Hongjia Yang; Chenxiao Yu; Zhengguang Wang; Jianing Cai; Junlong Aaron Zhou; Bolin Shen; Alex Qian; Weixin Chen; et al. (CoRR, 2024)

Federated Graph Learning with Graphless Clients. - Xingbo Fu; Song Wang 013; Yushun Dong; Binchi Zhang; Chen Chen 022; Jundong Li (Trans. Mach. Learn. Res., 2024)

Learning Hierarchical Task Structures for Few-shot Graph Classification. - Song Wang 013; Yushun Dong; Xiao Huang 001; Chen Chen 022; Jundong Li (ACM Trans. Knowl. Discov. Data, 2024)

ST-FiT: Inductive Spatial-Temporal Forecasting with Limited Training Data. - Zhenyu Lei 004; Yushun Dong; Jundong Li; Chen Chen 022 (AAAI, 2025)

BrainMAP: Learning Multiple Activation Pathways in Brain Networks. - Song Wang 013; Zhenyu Lei 004; Zhen Tan 001; Jiaqi Ding; Xinyu Zhao; Yushun Dong; Guorong Wu 001; Tianlong Chen 001; Chen Chen 022; Aiying Zhang; Jundong Li (AAAI, 2025)

Harnessing Large Language Models for Disaster Management: A Survey. - Zhenyu Lei 004; Yushun Dong; Weiyu Li; Rong Ding; Qi R. Wang; Jundong Li (ACL (Findings), 2025)

Graph Neural Networks Are More Than Filters: Revisiting and Benchmarking from A Spectral Perspective. - Yushun Dong; Patrick Soga; Yinhan He; Song Wang 013; Jundong Li (ICLR, 2025)

CEB: Compositional Evaluation Benchmark for Fairness in Large Language Models. - Song Wang 013; Peng Wang 105; Tong Zhou; Yushun Dong; Zhen Tan 001; Jundong Li (ICLR, 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 001; Zhuo Xiao; Wanghao Ye; Yichi Zhang; Yushun Dong; et al. (WWW (Companion Volume), 2025)

Harnessing Large Language Models for Disaster Management: A Survey. - Zhenyu Lei 004; Yushun Dong; Weiyu Li; Rong Ding; Qi Wang; Jundong Li (CoRR, 2025)

A Survey of Model Extraction Attacks and Defenses in Distributed Computing Environments. - Kaixiang Zhao; Lincan Li; Kaize Ding; Neil Zhenqiang Gong; Yue Zhao 016; Yushun Dong (CoRR, 2025)

ExPath: Towards Explaining Targeted Pathways for Biological Knowledge Bases. - Rikuto Kotoge; Ziwei Yang 002; Zheng Chen 012; Yushun Dong; Yasuko Matsubara; Jimeng Sun 001; Yasushi Sakurai (CoRR, 2025)

Generative AI in Transportation Planning: A Survey. - Longchao Da; Tiejin Chen; Zhuoheng Li; Shreyas Bachiraju; Huaiyuan Yao; Li Li 006; Yushun Dong; Xiyang Hu; Zhengzhong Tu; Dongjie Wang; Yue Zhao 016; Xuanyu Zhou; et al. (CoRR, 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, 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 016 (CoRR, 2025)

Measuring Computational Universality of Fully Homomorphic Encryption. - Jiaqi Xue; Xin Xin; Wei Zhang 056; Mengxin Zheng; Qianqian Song; Minxuan Zhou; Yushun Dong; Dongjie Wang; Xun Chen; Jiafeng Xie; Liqiang Wang; David Mohaisen; et al. (CoRR, 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 016 (CoRR, 2025)

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs. - Zihan Chen 002; Xingbo Fu; Yushun Dong; Jundong Li; Cong Shen 001 (CoRR, 2025)

MISLEADER: Defending against Model Extraction with Ensembles of Distilled Models. - Xueqi Cheng; Minxing Zheng; Shixiang Zhu; Yushun Dong (CoRR, 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, 2025)

TyphoFormer: Language-Augmented Transformer for Accurate Typhoon Track Forecasting. - Lincan Li; Eren Erman Ozguven; Yue Zhao 016; Guang Wang; Yiqun Xie; Yushun Dong (CoRR, 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, 2025)

Learning from the Storm: A Multivariate Machine Learning Approach to Predicting Hurricane-Induced Economic Losses. - Bolin Shen; Eren Erman Ozguven; Yue Zhao 016; Guang Wang; Yiqun Xie; Yushun Dong (CoRR, 2025)

A Survey on Model Extraction Attacks and Defenses for Large Language Models. - Kaixiang Zhao; Lincan Li; Kaize Ding; Neil Zhenqiang Gong; Yue Zhao 016; Yushun Dong (CoRR, 2025)

DESIGN: Encrypted GNN Inference via Server-Side Input Graph Pruning. - Kaixiang Zhao; Joseph Yousry Attalla; Qian Lou; Yushun Dong (CoRR, 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 016; Yushun Dong (CoRR, 2025)