| 2025 | ICML | PARM: Multi-Objective Test-Time Alignment via Preference-Aware Autoregressive Reward Model. | Baijiong Lin, Weisen Jiang, Yuancheng Xu, Hao Chen, Ying-Cong Chen |
| 2024 | ACL | Forward-Backward Reasoning in Large Language Models for Mathematical Verification. | Weisen Jiang, Han Shi, Longhui Yu, Zhengying Liu, Yu Zhang, Zhenguo Li, James T. Kwok |
| 2024 | ECCV | Learning Scalable Model Soup on a Single GPU: An Efficient Subspace Training Strategy. | Tao Li, Weisen Jiang, Fanghui Liu, Xiaolin Huang, James T. Kwok |
| 2024 | ECCV | MTMamba: Enhancing Multi-task Dense Scene Understanding by Mamba-Based Decoders. | Baijiong Lin, Weisen Jiang, Pengguang Chen, Yu Zhang, Shu Liu, Ying-Cong Chen |
| 2024 | ICLR | MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models. | Longhui Yu, Weisen Jiang, Han Shi, Jincheng Yu, Zhengying Liu, Yu Zhang, James T. Kwok, Zhenguo Li, Adrian Weller, Weiyang Liu |
| 2023 | ICLR | An Adaptive Policy to Employ Sharpness-Aware Minimization. | Weisen Jiang, Hansi Yang, Yu Zhang, James T. Kwok |
| 2023 | ICML | Effective Structured Prompting by Meta-Learning and Representative Verbalizer. | Weisen Jiang, Yu Zhang, James T. Kwok |
| 2022 | ICML | Subspace Learning for Effective Meta-Learning. | Weisen Jiang, James T. Kwok, Yu Zhang |
| 2021 | IJCNN | SEEN: Few-Shot Classification with SElf-ENsemble. | Weisen Jiang, Yu Zhang, James T. Kwok |