| 2025 | IJCNN | Simple yet Effective Gradient-Free Graph Convolutional Networks. | Yulin Zhu, Xing Ai, Qimai Li, Xiaoming Wu, Wai-Lun Lo, Kai Zhou |
| 2023 | ICLR | Recon: Reducing Conflicting Gradients From the Root For Multi-Task Learning. | Guangyuan Shi, Qimai Li, Wenlong Zhang, Jiaxin Chen, Xiao-Ming Wu |
| 2023 | IJCAI | Boosting Decision-Based Black-Box Adversarial Attack with Gradient Priors. | Han Liu, Xingshuo Huang, Xiaotong Zhang, Qimai Li, Fenglong Ma, Wei Wang, Hongyang Chen, Hong Yu, Xianchao Zhang |
| 2022 | WWW | Modeling User Behavior with Graph Convolution for Personalized Product Search. | Lu Fan, Qimai Li, Bo Liu, Xiao-Ming Wu, Xiaotong Zhang, Fuyu Lv, Guli Lin, Sen Li, Taiwei Jin, Keping Yang |
| 2021 | KDD | Dimensionwise Separable 2-D Graph Convolution for Unsupervised and Semi-Supervised Learning on Graphs. | Qimai Li, Xiaotong Zhang, Han Liu, Quanyu Dai, Xiao-Ming Wu |
| 2020 | ACL | Unknown Intent Detection Using Gaussian Mixture Model with an Application to Zero-shot Intent Classification. | Guangfeng Yan, Lu Fan, Qimai Li, Han Liu, Xiaotong Zhang, Xiao-Ming Wu, Albert Y. S. Lam |
| 2019 | CVPR | Label Efficient Semi-Supervised Learning via Graph Filtering. | Qimai Li, Xiao-Ming Wu, Han Liu, Xiaotong Zhang, Zhichao Guan |
| 2019 | EMNLP | Reconstructing Capsule Networks for Zero-shot Intent Classification. | Han Liu, Xiaotong Zhang, Lu Fan, Xuandi Fu, Qimai Li, Xiao-Ming Wu, Albert Y. S. Lam |
| 2019 | IJCAI | Attributed Graph Clustering via Adaptive Graph Convolution. | Xiaotong Zhang, Han Liu, Qimai Li, Xiao-Ming Wu |
| 2018 | AAAI | Deeper Insights Into Graph Convolutional Networks for Semi-Supervised Learning. | Qimai Li, Zhichao Han, Xiao-Ming Wu |