Jintang Li

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 51

Top Topics

Partial Knowledge

Top Venues

Publications

Yuchang Zhu, Jintang Li, Liang Chen, Zibin Zheng
The Devil is in the Data: Learning Fair Graph Neural Networks via Partial Knowledge Distillation. WSDM (2024)
Yunfei Liu, Jintang Li, Yuehe Chen, Ruofan Wu, Ericbk Wang, Jing Zhou, Sheng Tian, Shuheng Shen, Xing Fu, Changhua Meng, Weiqiang Wang, Liang Chen
Revisiting Modularity Maximization for Graph Clustering: A Contrastive Learning Perspective. KDD (2024)
Yuchang Zhu, Jintang Li, Yatao Bian, Zibin Zheng, Liang Chen
One Fits All: Learning Fair Graph Neural Networks for Various Sensitive Attributes. KDD (2024)
Xinzhou Jin, Jintang Li, Liang Chen, Chenyun Yu, Yuanzhen Xie, Tao Xie, Chengxiang Zhuo, Zang Li, Zibin Zheng
CL: Embarrassingly Simple Layer-to-Layer Contrastive Learning for Graph Collaborative Filtering. CoRR (2024)
Zulun Zhu, Kai Wang, Haoyu Liu, Jintang Li, Siqiang Luo
Topology-monitorable Contrastive Learning on Dynamic Graphs. KDD (2024)
Huizhe Zhang, Jintang Li, Liang Chen, Zibin Zheng
SGHormer: An Energy-Saving Graph Transformer Driven by Spikes. CoRR (2024)
Yunfei Liu, Jintang Li, Yuehe Chen, Ruofan Wu, Ericbk Wang, Jing Zhou, Sheng Tian, Shuheng Shen, Xing Fu, Changhua Meng, Weiqiang Wang, Liang Chen
Revisiting Modularity Maximization for Graph Clustering: A Contrastive Learning Perspective. CoRR (2024)
Jintang Li, Ruofan Wu, Xinzhou Jin, Boqun Ma, Liang Chen, Zibin Zheng
State Space Models on Temporal Graphs: A First-Principles Study. CoRR (2024)
Yuchang Zhu, Jintang Li, Zibin Zheng, Liang Chen
Fair Graph Representation Learning via Sensitive Attribute Disentanglement. WWW (2024)
Yuchang Zhu, Jintang Li, Yatao Bian, Zibin Zheng, Liang Chen
One Fits All: Learning Fair Graph Neural Networks for Various Sensitive Attributes. CoRR (2024)
Jintang Li, Huizhe Zhang, Ruofan Wu, Zulun Zhu, Baokun Wang, Changhua Meng, Zibin Zheng, Liang Chen
A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks. ICLR (2024)
Yuchang Zhu, Jintang Li, Zibin Zheng, Liang Chen
Fair Graph Representation Learning via Sensitive Attribute Disentanglement. CoRR (2024)
Wangbin Sun, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian, Zibin Zheng
Rethinking and Simplifying Bootstrapped Graph Latents. WSDM (2024)
Jintang Li, Jiaying Peng, Liang Chen, Zibin Zheng, Tingting Liang, Qing Ling
Spectral Adversarial Training for Robust Graph Neural Network. IEEE Trans. Knowl. Data Eng. 35 (9) (2023)
Jintang Li, Tao Xie, Liang Chen, Fenfang Xie, Xiangnan He, Zibin Zheng
Adversarial Attack on Large Scale Graph. IEEE Trans. Knowl. Data Eng. 35 (1) (2023)
Xinzhou Jin, Jintang Li, Yuanzhen Xie, Liang Chen, Beibei Kong, Lei Cheng, Bo Hu, Zang Li, Zibin Zheng
Enhancing Graph Collaborative Filtering via Neighborhood Structure Embedding. ICDM (2023)
Jie Liao, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian, Zibin Zheng
SAILOR: Structural Augmentation Based Tail Node Representation Learning. CoRR (2023)
Jintang Li, Zheng Wei, Jiawang Dan, Jing Zhou, Yuchang Zhu, Ruofan Wu, Baokun Wang, Zhang Zhen, Changhua Meng, Hong Jin, Zibin Zheng, Liang Chen
Hetero$^2$Net: Heterophily-aware Representation Learning on Heterogenerous Graphs. CoRR (2023)
Jintang Li, Sheng Tian, Ruofan Wu, Liang Zhu, Welong Zhao, Changhua Meng, Liang Chen, Zibin Zheng, Hongzhi Yin
Less Can Be More: Unsupervised Graph Pruning for Large-scale Dynamic Graphs. CoRR (2023)
Jintang Li, Huizhe Zhang, Ruofan Wu, Zulun Zhu, Liang Chen, Zibin Zheng, Baokun Wang, Changhua Meng
A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks. CoRR (2023)
Wangbin Sun, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian, Zibin Zheng
Rethinking and Simplifying Bootstrapped Graph Latents. CoRR (2023)
Sheng Tian, Jihai Dong, Jintang Li, Wenlong Zhao, Xiaolong Xu, Baokun Wang, Bowen Song, Changhua Meng, Tianyi Zhang, Liang Chen
SAD: Semi-Supervised Anomaly Detection on Dynamic Graphs. IJCAI (2023)
Jintang Li, Jie Liao, Ruofan Wu, Liang Chen, Zibin Zheng, Jiawang Dan, Changhua Meng, Weiqiang Wang
GUARD: Graph Universal Adversarial Defense. CIKM (2023)
Yuchang Zhu, Jintang Li, Liang Chen, Zibin Zheng
The Devil is in the Data: Learning Fair Graph Neural Networks via Partial Knowledge Distillation. CoRR (2023)
Jintang Li, Wangbin Sun, Ruofan Wu, Yuchang Zhu, Liang Chen, Zibin Zheng
Scaling Up, Scaling Deep: Blockwise Graph Contrastive Learning. CoRR (2023)
Jie Liao, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian, Zibin Zheng
SAILOR: Structural Augmentation Based Tail Node Representation Learning. CIKM (2023)
Sheng Tian, Jihai Dong, Jintang Li, Wenlong Zhao, Xiaolong Xu, Baokun Wang, Bowen Song, Changhua Meng, Tianyi Zhang, Liang Chen
SAD: Semi-Supervised Anomaly Detection on Dynamic Graphs. CoRR (2023)
Jintang Li, Ruofan Wu, Wangbin Sun, Liang Chen, Sheng Tian, Liang Zhu, Changhua Meng, Zibin Zheng, Weiqiang Wang
What's Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders. KDD (2023)
Jintang Li, Zhouxin Yu, Zulun Zhu, Liang Chen, Qi Yu, Zibin Zheng, Sheng Tian, Ruofan Wu, Changhua Meng
Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks. AAAI (2023)
Jintang Li, Jiawang Dan, Ruofan Wu, Jing Zhou, Sheng Tian, Yunfei Liu, Baokun Wang, Changhua Meng, Weiqiang Wang, Yuchang Zhu, Liang Chen, Zibin Zheng
LasTGL: An Industrial Framework for Large-Scale Temporal Graph Learning. CoRR (2023)
Jintang Li, Jiaying Peng, Liang Chen, Zibin Zheng, Tingting Liang, Qing Ling
Spectral Adversarial Training for Robust Graph Neural Network. CoRR (2022)
Jintang Li, Jie Liao, Ruofan Wu, Liang Chen, Changhua Meng, Zibin Zheng, Weiqiang Wang
GUARD: Graph Universal Adversarial Defense. CoRR (2022)
Jintang Li, Ruofan Wu, Wangbin Sun, Liang Chen, Sheng Tian, Liang Zhu, Changhua Meng, Zibin Zheng, Weiqiang Wang
MaskGAE: Masked Graph Modeling Meets Graph Autoencoders. CoRR (2022)
Bingzhe Wu, Jintang Li, Chengbin Hou, Guoji Fu, Yatao Bian, Liang Chen, Junzhou Huang
Recent Advances in Reliable Deep Graph Learning: Adversarial Attack, Inherent Noise, and Distribution Shift. CoRR (2022)
Zishan Gu, Jintang Li, Liang Chen
Are All Edges Necessary? A Unified Framework for Graph Purification. CoRR (2022)
Bingzhe Wu, Jintang Li, Junchi Yu, Yatao Bian, Hengtong Zhang, Chaochao Chen, Chengbin Hou, Guoji Fu, Liang Chen, Tingyang Xu, Yu Rong, Xiaolin Zheng, Junzhou Huang, Ran He, Baoyuan Wu, Guangyu Sun, Peng Cui, Zibin Zheng, Zhe Liu, Peilin Zhao
A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection. CoRR (2022)
Bingzhe Wu, Yatao Bian, Hengtong Zhang, Jintang Li, Junchi Yu, Liang Chen, Chaochao Chen, Junzhou Huang
Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection. KDD (2022)
Zulun Zhu, Jiaying Peng, Jintang Li, Liang Chen, Qi Yu, Siqiang Luo
Spiking Graph Convolutional Networks. IJCAI (2022)
Zulun Zhu, Jiaying Peng, Jintang Li, Liang Chen, Qi Yu, Siqiang Luo
Spiking Graph Convolutional Networks. CoRR (2022)
Liang Chen, Qibiao Peng, Jintang Li, Yang Liu, Jiawei Chen, Yong Li, Zibin Zheng
Neighboring Backdoor Attacks on Graph Convolutional Network. CoRR (2022)
Zhouxin Yu, Jintang Li, Liang Chen, Zibin Zheng
Unifying multi-associations through hypergraph for bundle recommendation. Knowl. Based Syst. 255 (2022)
Liang Chen, Tao Xie, Jintang Li, Zibin Zheng
Graph Enhanced Neural Interaction Model for recommendation. Knowl. Based Syst. 246 (2022)
Jintang Li, Zhouxin Yu, Zulun Zhu, Liang Chen, Qi Yu, Zibin Zheng, Sheng Tian, Ruofan Wu, Changhua Meng
Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks. CoRR (2022)
Liang Chen, Jiaying Peng, Yang Liu, Jintang Li, Fenfang Xie, Zibin Zheng
Phishing Scams Detection in Ethereum Transaction Network. ACM Trans. Internet Techn. 21 (1) (2021)
Liang Chen, Jintang Li, Qibiao Peng, Yang Liu, Zibin Zheng, Carl Yang
Understanding Structural Vulnerability in Graph Convolutional Networks. IJCAI (2021)
Liang Chen, Jintang Li, Qibiao Peng, Yang Liu, Zibin Zheng, Carl Yang
Understanding Structural Vulnerability in Graph Convolutional Networks. CoRR (2021)
Jintang Li, Kun Xu, Liang Chen, Zibin Zheng, Xiao Liu
GraphGallery: A Platform for Fast Benchmarking and Easy Development of Graph Neural Networks Based Intelligent Software. ICSE (Companion Volume) (2021)
Jintang Li, Kun Xu, Liang Chen, Zibin Zheng, Xiao Liu
GraphGallery: A Platform for Fast Benchmarking and Easy Development of Graph Neural Networks Based Intelligent Software. CoRR (2021)
Jintang Li, Tao Xie, Liang Chen, Fenfang Xie, Xiangnan He, Zibin Zheng
Adversarial Attack on Large Scale Graph. CoRR (2020)
Liang Chen, Jintang Li, Jiaying Peng, Tao Xie, Zengxu Cao, Kun Xu, Xiangnan He, Zibin Zheng
A Survey of Adversarial Learning on Graphs. CoRR (2020)
Jintang Li, Zishan Gu, Qibiao Peng, Kun Xu, Liang Chen, Zibin Zheng
Deep Insights into Graph Adversarial Learning: An Empirical Study Perspective. HBAI@IJCAI (2020)