| 2025 | AAAI | Towards Macro-AUC Oriented Imbalanced Multi-Label Continual Learning. | Yan Zhang, Guoqiang Wu, Bingzheng Wang, Teng Pang, Haoliang Sun, Yilong Yin |
| 2025 | ICASSP | N3C: Towards Replay-based Novelty Continual Clustering with Class-Overlapping. | Yan Zhang, Guoqiang Wu, Bingzheng Wang, Teng Pang, Yilong Yin |
| 2025 | ICML | A Theory for Conditional Generative Modeling on Multiple Data Sources. | Rongzhen Wang, Yan Zhang, Chenyu Zheng, Chongxuan Li, Guoqiang Wu |
| 2024 | AAAI | DiffAIL: Diffusion Adversarial Imitation Learning. | Bingzheng Wang, Guoqiang Wu, Teng Pang, Yan Zhang, Yilong Yin |
| 2024 | EMNLP | IPL: Leveraging Multimodal Large Language Models for Intelligent Product Listing. | Kang Chen, Qingheng Zhang, Chengbao Lian, Yixin Ji, Xuwei Liu, Shuguang Han, Guoqiang Wu, Fei Huang, Jufeng Chen |
| 2023 | ACML | Can Infinitely Wide Deep Nets Help Small-data Multi-label Learning? | Guoqiang Wu, Jun Zhu |
| 2023 | ICML | Towards Understanding Generalization of Macro-AUC in Multi-label Learning. | Guoqiang Wu, Chongxuan Li, Yilong Yin |
| 2023 | ICML | Revisiting Discriminative vs. Generative Classifiers: Theory and Implications. | Chenyu Zheng, Guoqiang Wu, Fan Bao, Yue Cao, Chongxuan Li, Jun Zhu |
| 2018 | ICPR | Privileged Multi-Target Support Vector Regression. | Guoqiang Wu, Yingjie Tian, Dalian Liu |