Jintang Li
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
21
Venues
11
Active years
2020–2026
Best venue rank
A*
Where they publish
Papers
21 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | AAAI | GT-SNT: A Linear-Time Transformer for Large-Scale Graphs via Spiking Node Tokenization. | Huizhe Zhang, Jintang Li, Yuchang Zhu, Huazhen Zhong, Liang Chen |
| 2025 | ICASSP | AP-Net: Semi-Supervised Ultrasound Cardiac Segmentation Using Enhanced Anatomical Prior. | Yuhuan Lu, Jintang Li, Jianxin Lin, Ying Yuan, Jagath C. Rajapakse, Ningbo Zhu, Chunlian Wang, Kenli Li |
| 2025 | ICML | Measuring Diversity in Synthetic Datasets. | Yuchang Zhu, Huizhe Zhang, Bingzhe Wu, Jintang Li, Zibin Zheng, Peilin Zhao, Liang Chen, Yatao Bian |
| 2024 | ICLR | A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks. | Jintang Li, Huizhe Zhang, Ruofan Wu, Zulun Zhu, Baokun Wang, Changhua Meng, Zibin Zheng, Liang Chen |
| 2024 | KDD | Revisiting Modularity Maximization for Graph Clustering: A Contrastive Learning Perspective. | Yunfei Liu, Jintang Li, Yuehe Chen, Ruofan Wu, Ericbk Wang, Jing Zhou, Sheng Tian, Shuheng Shen, Xing Fu, Changhua Meng, Weiqiang Wang, Liang Chen |
| 2024 | KDD | One Fits All: Learning Fair Graph Neural Networks for Various Sensitive Attributes. | Yuchang Zhu, Jintang Li, Yatao Bian, Zibin Zheng, Liang Chen |
| 2024 | KDD | Topology-monitorable Contrastive Learning on Dynamic Graphs. | Zulun Zhu, Kai Wang, Haoyu Liu, Jintang Li, Siqiang Luo |
| 2024 | WWW | Fair Graph Representation Learning via Sensitive Attribute Disentanglement. | Yuchang Zhu, Jintang Li, Zibin Zheng, Liang Chen |
| 2024 | WSDM | Rethinking and Simplifying Bootstrapped Graph Latents. | Wangbin Sun, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian, Zibin Zheng |
| 2024 | WSDM | The Devil is in the Data: Learning Fair Graph Neural Networks via Partial Knowledge Distillation. | Yuchang Zhu, Jintang Li, Liang Chen, Zibin Zheng |
| 2023 | AAAI | Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks. | Jintang Li, Zhouxin Yu, Zulun Zhu, Liang Chen, Qi Yu, Zibin Zheng, Sheng Tian, Ruofan Wu, Changhua Meng |
| 2023 | CIKM | SAILOR: Structural Augmentation Based Tail Node Representation Learning. | Jie Liao, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian, Zibin Zheng |
| 2023 | CIKM | GUARD: Graph Universal Adversarial Defense. | Jintang Li, Jie Liao, Ruofan Wu, Liang Chen, Zibin Zheng, Jiawang Dan, Changhua Meng, Weiqiang Wang |
| 2023 | ICDM | Enhancing Graph Collaborative Filtering via Neighborhood Structure Embedding. | Xinzhou Jin, Jintang Li, Yuanzhen Xie, Liang Chen, Beibei Kong, Lei Cheng, Bo Hu, Zang Li, Zibin Zheng |
| 2023 | IJCAI | SAD: Semi-Supervised Anomaly Detection on Dynamic Graphs. | Sheng Tian, Jihai Dong, Jintang Li, Wenlong Zhao, Xiaolong Xu, Baokun Wang, Bowen Song, Changhua Meng, Tianyi Zhang, Liang Chen |
| 2023 | KDD | What's Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders. | Jintang Li, Ruofan Wu, Wangbin Sun, Liang Chen, Sheng Tian, Liang Zhu, Changhua Meng, Zibin Zheng, Weiqiang Wang |
| 2022 | IJCAI | Spiking Graph Convolutional Networks. | Zulun Zhu, Jiaying Peng, Jintang Li, Liang Chen, Qi Yu, Siqiang Luo |
| 2022 | KDD | Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection. | Bingzhe Wu, Yatao Bian, Hengtong Zhang, Jintang Li, Junchi Yu, Liang Chen, Chaochao Chen, Junzhou Huang |
| 2021 | IJCAI | Understanding Structural Vulnerability in Graph Convolutional Networks. | Liang Chen, Jintang Li, Qibiao Peng, Yang Liu, Zibin Zheng, Carl Yang |
| 2021 | ICSE | GraphGallery: A Platform for Fast Benchmarking and Easy Development of Graph Neural Networks Based Intelligent Software. | Jintang Li, Kun Xu, Liang Chen, Zibin Zheng, Xiao Liu |
| 2020 | IJCAI | Deep Insights into Graph Adversarial Learning: An Empirical Study Perspective. | Jintang Li, Zishan Gu, Qibiao Peng, Kun Xu, Liang Chen, Zibin Zheng |