Graph Structure Learning for Robust Graph Neural Networks. - Wei Jin 009; Yao Ma 001; Xiaorui Liu; Xianfeng Tang; Suhang Wang; Jiliang Tang (KDD, 2020)

Adversarial Attacks and Defenses: Frontiers, Advances and Practice. - Han Xu 002; Yaxin Li 001; Wei Jin 009; Jiliang Tang (KDD, 2020)

Traffic Flow Prediction via Spatial Temporal Graph Neural Network. - Xiaoyang Wang; Yao Ma 001; Yiqi Wang 001; Wei Jin 009; Xin Wang 035; Jiliang Tang; Caiyan Jia; Jian Yu 001 (WWW, 2020)

Adversarial Attacks and Defenses on Graphs: A Review and Empirical Study. - Wei Jin 009; Yaxin Li 001; Han Xu 002; Yiqi Wang 001; Jiliang Tang (CoRR, 2020)

DeepRobust: A PyTorch Library for Adversarial Attacks and Defenses. - Yaxin Li 001; Wei Jin 009; Han Xu 002; Jiliang Tang (CoRR, 2020)

Self-supervised Learning on Graphs: Deep Insights and New Direction. - Wei Jin 009; Tyler Derr; Haochen Liu; Yiqi Wang 001; Suhang Wang; Zitao Liu 001; Jiliang Tang (CoRR, 2020)

Adversarial Attacks and Defenses on Graphs. - Wei Jin 009; Yaxin Li 001; Han Xu 002; Yiqi Wang 001; Shuiwang Ji; Charu Aggarwal 001; Jiliang Tang (SIGKDD Explor., 2020)

DeepRobust: a Platform for Adversarial Attacks and Defenses. - Yaxin Li 001; Wei Jin 009; Han Xu 002; Jiliang Tang (AAAI, 2021)

The Authors Matter: Understanding and Mitigating Implicit Bias in Deep Text Classification. - Haochen Liu; Wei Jin 009; Hamid Karimi; Zitao Liu 001; Jiliang Tang (ACL/IJCNLP (Findings), 2021)

Graph Feature Gating Networks. - Wei Jin 009; Xiaorui Liu; Yao Ma 001; Tyler Derr; Charu C. Aggarwal; Jiliang Tang (CIKM, 2021)

Elastic Graph Neural Networks. - Xiaorui Liu; Wei Jin 009; Yao Ma 001; Yaxin Li 001; Hua Liu; Yiqi Wang 001; Ming Yan 006; Jiliang Tang (ICML, 2021)

Graph Representation Learning: Foundations, Methods, Applications and Systems. - Wei Jin 009; Yao Ma 001; Yiqi Wang 001; Xiaorui Liu; Jiliang Tang; Yukuo Cen; Jiezhong Qiu; Jie Tang 001; Chuan Shi 001; Yanfang Ye 001; Jiawei Zhang 001; Philip S. Yu (KDD, 2021)

Graph Neural Networks with Adaptive Residual. - Xiaorui Liu; Jiayuan Ding; Wei Jin 009; Han Xu 002; Yao Ma 001; Zitao Liu 001; Jiliang Tang (NeurIPS, 2021)

Graph Mining with Graph Neural Networks. - Wei Jin 009 (WSDM, 2021)

Node Similarity Preserving Graph Convolutional Networks. - Wei Jin 009; Tyler Derr; Yiqi Wang 001; Yao Ma 001; Zitao Liu 001; Jiliang Tang (WSDM, 2021)

Localized Graph Collaborative Filtering. - Yiqi Wang 001; Chaozhuo Li; Mingzheng Li; Wei Jin 009; Yuming Liu; Hao Sun 015; Xing Xie 001 (CoRR, 2021)

Graph Trend Networks for Recommendations. - Wenqi Fan; Xiaorui Liu; Wei Jin 009; Xiangyu Zhao 001; Jiliang Tang; Qing Li 001 (CoRR, 2021)

Automated Self-Supervised Learning for Graphs. - Wei Jin 009; Xiaorui Liu; Xiangyu Zhao 001; Yao Ma 001; Neil Shah; Jiliang Tang (ICLR, 2022)

Graph Condensation for Graph Neural Networks. - Wei Jin 009; Lingxiao Zhao; Shichang Zhang; Yozen Liu; Jiliang Tang; Neil Shah (ICLR, 2022)

From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness. - Lingxiao Zhao; Wei Jin 009; Leman Akoglu; Neil Shah (ICLR, 2022)

Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective. - Wei Jin 009; Xiaorui Liu; Yao Ma 001; Charu C. Aggarwal; Jiliang Tang (KDD, 2022)

Condensing Graphs via One-Step Gradient Matching. - Wei Jin 009; Xianfeng Tang; Haoming Jiang; Zheng Li 018; Danqing Zhang; Jiliang Tang; Bing Yin (KDD, 2022)

Graph Neural Networks for Multimodal Single-Cell Data Integration. - Hongzhi Wen; Jiayuan Ding; Wei Jin 009; Yiqi Wang 001; Yuying Xie 001; Jiliang Tang (KDD, 2022)

Localized Graph Collaborative Filtering. - Yiqi Wang 001; Chaozhuo Li; Mingzheng Li; Wei Jin 009; Yuming Liu; Hao Sun 015; Xing Xie 001; Jiliang Tang (SDM, 2022)

Graph Trend Filtering Networks for Recommendation. - Wenqi Fan; Xiaorui Liu; Wei Jin 009; Xiangyu Zhao 001; Jiliang Tang; Qing Li 001 (SIGIR, 2022)

Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels. - Enyan Dai; Wei Jin 009; Hui Liu 031; Suhang Wang (WSDM, 2022)

Graph Neural Networks for Multimodal Single-Cell Data Integration. - Hongzhi Wen; Jiayuan Ding; Wei Jin 009; Yuying Xie 001; Jiliang Tang (CoRR, 2022)

Condensing Graphs via One-Step Gradient Matching. - Wei Jin 009; Xianfeng Tang; Haoming Jiang; Zheng Li 018; Danqing Zhang; Jiliang Tang; Bin Ying (CoRR, 2022)

Learning Representations for Hyper-Relational Knowledge Graphs. - Harry Shomer; Wei Jin 009; Juan-Hui Li; Yao Ma 001; Jiliang Tang (CoRR, 2022)

Test-Time Training for Graph Neural Networks. - Yiqi Wang 001; Chaozhuo Li; Wei Jin 009; Rui Li 086; Jianan Zhao 002; Jiliang Tang; Xing Xie 001 (CoRR, 2022)

Learning Representations for Hyper-Relational Knowledge Graphs. - Harry Shomer; Wei Jin 009; Juanhui Li; Yao Ma 001; Hui Liu 031 (ASONAM, 2023)

Single-Cell Multimodal Prediction via Transformers. - Wenzhuo Tang; Hongzhi Wen; Renming Liu; Jiayuan Ding; Wei Jin 009; Yuying Xie 001; Hui Liu 031; Jiliang Tang (CIKM, 2023)

Jointly Attacking Graph Neural Network and its Explanations. - Wenqi Fan; Han Xu 002; Wei Jin 009; Xiaorui Liu; Xianfeng Tang; Suhang Wang; Qing Li 001; Jiliang Tang; Jianping Wang 001; Charu C. Aggarwal (ICDE, 2023)

Empowering Graph Representation Learning with Test-Time Graph Transformation. - Wei Jin 009; Tong Zhao 003; Jiayuan Ding; Yozen Liu; Jiliang Tang; Neil Shah (ICLR, 2023)

Enhancing Graph Representations Learning with Decorrelated Propagation. - Hua Liu; Haoyu Han 001; Wei Jin 009; Xiaorui Liu; Hui Liu 031 (KDD, 2023)

Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation. - Wei Jin 009; Haitao Mao; Zheng Li 018; Haoming Jiang; Chen Luo 003; Hongzhi Wen; Haoyu Han 001; Hanqing Lu; Zhengyang Wang; Ruirui Li 002; Zhen Li; Monica Xiao Cheng; et al. (NeurIPS, 2023)

Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All? - Haitao Mao; Zhikai Chen; Wei Jin 009; Haoyu Han 001; Yao Ma 001; Tong Zhao 003; Neil Shah; Jiliang Tang (NeurIPS, 2023)

Toward Degree Bias in Embedding-Based Knowledge Graph Completion. - Harry Shomer; Wei Jin 009; Wentao Wang 006; Jiliang Tang (WWW, 2023)

Single Cells Are Spatial Tokens: Transformers for Spatial Transcriptomic Data Imputation. - Hongzhi Wen; Wenzhuo Tang; Wei Jin 009; Jiayuan Ding; Renming Liu; Feng Shi; Yuying Xie 001; Jiliang Tang (CoRR, 2023)

Augment with Care: Enhancing Graph Contrastive Learning with Selective Spectrum Perturbation. - Kaiqi Yang 001; Haoyu Han 001; Wei Jin 009; Hui Liu 031 (CoRR, 2023)

Knowledge-Infused Prompting: Assessing and Advancing Clinical Text Data Generation with Large Language Models. - Ran Xu 002; Hejie Cui; Yue Yu 001; Xuan Kan; Wenqi Shi; Yuchen Zhuang; Wei Jin 009; Joyce C. Ho; Carl Yang 001 (CoRR, 2023)

Customized Graph Nerual Networks. - Yiqi Wang 001; Yao Ma 001; Wei Jin 009; Chaozhuo Li; Charu Aggarwal 001; Jiliang Tang (IEEE Data Eng. Bull., 2023)

Graph Data Augmentation for Graph Machine Learning: A Survey. - Tong Zhao 003; Wei Jin 009; Yozen Liu; Yingheng Wang; Gang Liu 025; Stephan Günnemann; Neil Shah; Meng Jiang 001 (IEEE Data Eng. Bull., 2023)

INS-GNN: Improving graph imbalance learning with self-supervision. - Xin Juan; Fengfeng Zhou; Wentao Wang 006; Wei Jin 009; Jiliang Tang; Xin Wang 035 (Inf. Sci., 2023)

Exploring the Potential of Large Language Models (LLMs)in Learning on Graphs. - Zhikai Chen; Haitao Mao; Hang Li 007; Wei Jin 009; Hongzhi Wen; Xiaochi Wei; Shuaiqiang Wang; Dawei Yin; Wenqi Fan; Hui Liu 031; Jiliang Tang (SIGKDD Explor., 2023)

Knowledge-Infused Prompting: Assessing and Advancing Clinical Text Data Generation with Large Language Models. - Ran Xu 002; Hejie Cui; Yue Yu 001; Xuan Kan; Wenqi Shi; Yuchen Zhuang; May Dongmei Wang; Wei Jin 009; Joyce C. Ho; Carl Yang 001 (ACL (Findings), 2024)

Trustworthy and Responsible AI for Information and Knowledge Management System. - Huaming Chen; Jun Zhuang; Yu Yao 005; Wei Jin 009; Haohan Wang; Yong Xie 002; Chi-Hung Chi; Kim-Kwang Raymond Choo (CIKM, 2024)

Spectral-Aware Augmentation for Enhanced Graph Representation Learning. - Kaiqi Yang 001; Haoyu Han 001; Wei Jin 009; Hui Liu 031 (CIKM, 2024)

Label-free Node Classification on Graphs with Large Language Models (LLMs). - Zhikai Chen; Haitao Mao; Hongzhi Wen; Haoyu Han 001; Wei Jin 009; Haiyang Zhang; Hui Liu 031; Jiliang Tang (ICLR, 2024)

CellPLM: Pre-training of Cell Language Model Beyond Single Cells. - Hongzhi Wen; Wenzhuo Tang; Xinnan Dai; Jiayuan Ding; Wei Jin 009; Yuying Xie 001; Jiliang Tang (ICLR, 2024)

A Comprehensive Survey on Graph Reduction: Sparsification, Coarsening, and Condensation. - Mohammad Hashemi; Shengbo Gong; Juntong Ni; Wenqi Fan; B. Aditya Prakash; Wei Jin 009 (IJCAI, 2024)

Investigating Out-of-Distribution Generalization of GNNs: An Architecture Perspective. - Kai Guo 003; Hongzhi Wen; Wei Jin 009; Yaming Guo; Jiliang Tang; Yi Chang 001 (KDD, 2024)

A Review of Graph Neural Networks in Epidemic Modeling. - Zewen Liu 005; Guancheng Wan; B. Aditya Prakash; Max S. Y. Lau; Wei Jin 009 (KDD, 2024)

Sub-Graph Based Diffusion Model for Link Prediction. - Hang Li 007; Wei Jin 009; Geri Skenderi; Harry Shomer; Wenzhuo Tang; Wenqi Fan; Jiliang Tang (LoG, 2024)

A Pure Transformer Pretraining Framework on Text-Attributed Graphs. - Yu Song; Haitao Mao; Jiachen Xiao; Jingzhe Liu; Zhikai Chen; Wei Jin 009; Carl Yang 001; Jiliang Tang; Hui Liu 031 (LoG, 2024)

Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights. - Zhikai Chen; Haitao Mao; Jingzhe Liu; Yu Song; Bingheng Li; Wei Jin 009; Bahare Fatemi; Anton Tsitsulin; Bryan Perozzi; Hui Liu 031; Jiliang Tang (NeurIPS, 2024)

DCAI: Data-centric Artificial Intelligence. - Wei Jin 009; Haohan Wang; Daochen Zha; Qiaoyu Tan; Yao Ma 001; Sharon Li 001; Su-In Lee (WWW (Companion Volume), 2024)

Globally Interpretable Graph Learning via Distribution Matching. - Yi Nian; Yurui Chang; Wei Jin 009; Lu Lin 001 (WWW, 2024)

Enhancing ID and Text Fusion via Alternative Training in Session-based Recommendation. - Juanhui Li; Haoyu Han 001; Zhikai Chen; Harry Shomer; Wei Jin 009; Amin Javari; Jiliang Tang (CoRR, 2024)

Enabling On-Device Learning via Experience Replay with Efficient Dataset Condensation. - Gelei Xu; Ningzhi Tang; Jun Xia 003; Wei Jin 009; Yiyu Shi 001 (CoRR, 2024)

EpiLearn: A Python Library for Machine Learning in Epidemic Modeling. - Zewen Liu 005; Yunxiao Li; Mingyang Wei; Guancheng Wan; Max S. Y. Lau; Wei Jin 009 (CoRR, 2024)

GC-Bench: A Benchmark Framework for Graph Condensation with New Insights. - Shengbo Gong; Juntong Ni; Noveen Sachdeva; Carl Yang 001; Wei Jin 009 (CoRR, 2024)

Learning on Graphs with Large Language Models(LLMs): A Deep Dive into Model Robustness. - Kai Guo 003; Zewen Liu 005; Zhikai Chen; Hongzhi Wen; Wei Jin 009; Jiliang Tang; Yi Chang 001 (CoRR, 2024)

Epidemiology-Aware Neural ODE with Continuous Disease Transmission Graph. - Guancheng Wan; Zewen Liu 005; Max S. Y. Lau; B. Aditya Prakash; Wei Jin 009 (CoRR, 2024)

SpatialCTD: A Large-Scale Tumor Microenvironment Spatial Transcriptomic Dataset to Evaluate Cell Type Deconvolution for Immuno-Oncology. - Jiayuan Ding; Lingxiao Li; Qiaolin Lu; Julian Venegas; Yixin Wang 003; Lidan Wu; Wei Jin 009; Hongzhi Wen; Renming Liu; Wenzhuo Tang; Xinnan Dai; Zhaoheng Li; et al. (J. Comput. Biol., 2024)

Deep Learning in Single-cell Analysis. - Dylan Molho; Jiayuan Ding; Wenzhuo Tang; Zhaoheng Li; Hongzhi Wen; Yixin Wang 003; Julian Venegas; Wei Jin 009; Renming Liu; Runze Su; Patrick Danaher; Robert Yang; et al. (ACM Trans. Intell. Syst. Technol., 2024)

Enabling Memory-Efficient On-Device Learning via Dataset Condensation. - Gelei Xu; Ningzhi Tang; Jun Xia 003; Ruiyang Qin; Wei Jin 009; Yiyu Shi 001 (DATE, 2025)

Precedence-Constrained Winter Value for Effective Graph Data Valuation. - Hongliang Chi; Wei Jin 009; Charu C. Aggarwal; Yao Ma 001 (ICLR, 2025)

Time Series Analysis in the Web: Recent Advances and Future Trends. - Ming Jin 005; Wei Jin 009; Hao Xue 001; Flora Salim; Yuxuan Liang (WWW (Companion Volume), 2025)

Efficient Epidemic Intervention Generation: A Graph Adversarial Attack Perspective. - Yunxiao Li; Mingyang Wei; Zewen Liu 005; Max S. Y. Lau; Wei Jin 009 (WWW (Companion Volume), 2025)

CAPE: Covariate-Adjusted Pre-Training for Epidemic Time Series Forecasting. - Zewen Liu 005; Juntong Ni; Max S. Y. Lau; Wei Jin 009 (CoRR, 2025)

TimeDistill: Efficient Long-Term Time Series Forecasting with MLP via Cross-Architecture Distillation. - Juntong Ni; Zewen Liu 005; Shiyu Wang 001; Ming Jin 005; Wei Jin 009 (CoRR, 2025)

Scalable Graph Condensation with Evolving Capabilities. - Shengbo Gong; Mohammad Hashemi; Juntong Ni; Carl Yang 001; Wei Jin 009 (CoRR, 2025)

Higher-order Interaction Matters: Dynamic Hypergraph Neural Networks for Epidemic Modeling. - Songyuan Liu; Shengbo Gong; Tianning Feng; Zewen Liu 005; Max S. Y. Lau; Wei Jin 009 (CoRR, 2025)

Graph ODEs and Beyond: A Comprehensive Survey on Integrating Differential Equations with Graph Neural Networks. - Zewen Liu 005; Xiaoda Wang; Bohan Wang; Zijie Huang 002; Carl Yang 001; Wei Jin 009 (CoRR, 2025)

TimeRecipe: A Time-Series Forecasting Recipe via Benchmarking Module Level Effectiveness. - Zhiyuan Zhao 002; Juntong Ni; Shangqing Xu; Haoxin Liu 001; Wei Jin 009; B. Aditya Prakash (CoRR, 2025)

Incorporating Rather Than Eliminating: Achieving Fairness for Skin Disease Diagnosis Through Group-Specific Expert. - Gelei Xu; Yuying Duan; Zheyuan Liu 010; Xueyang Li; Meng Jiang 001; Michael Lemmon 001; Wei Jin 009; Yiyu Shi 001 (CoRR, 2025)

Are We Overlooking the Dimensions? Learning Latent Hierarchical Channel Structure for High-Dimensional Time Series Forecasting. - Juntong Ni; Shiyu Wang 001; Zewen Liu 005; Xiaoming Shi 001; Xinyue Zhong; Zhou Ye 001; Wei Jin 009 (CoRR, 2025)

Beyond Chunks and Graphs: Retrieval-Augmented Generation through Triplet-Driven Thinking. - Shengbo Gong; Xianfeng Tang; Carl Yang 001; Wei Jin 009 (CoRR, 2025)

Can Large Language Models Adequately Perform Symbolic Reasoning Over Time Series? - Zewen Liu 005; Juntong Ni; Xianfeng Tang; Max S. Y. Lau; Wenpeng Yin 001; Wei Jin 009 (CoRR, 2025)