He is currently a Ph.D. student at School of Software Technology, Zhejiang University. His supervisor is Assistant Professor Haobo Wang. His major research interests generally lie in the area of machine learning and data intelligence, including black-box adaptation, low-resource methods, and large language models.

Education

• 09.2022-present Ph.D. candidate, School of Software Technology, Zhejiang University.
• 09.2018-06.2022 Bachelor of Computer Science and Technology, Beijing Jiaotong University.

Publications

• Mingxuan Xia, Haobo Wang, Yixuan Li, Zewei Yu, Jindong Wang, Junbo Zhao, Runze Wu. Prompt Candidates, then Distill: A Teacher-Student Framework for LLM-driven Data Annotation (ACL-Main 2025)
• Rui Wang, Mingxuan Xia, Haobo Wang, Lei Feng, Junbo Zhao, Gang Chen, Chang Yao. Towards Robust Incremental Learning under Ambiguous Supervision (IJCAI 2025)
• Ziquan Wang, Mingxuan Xia, Xiangyu Ren, Jiaqing Zhou, Gengyu Lyu, Tianlei Hu, and Haobo Wang. Multi-Instance Multi-Label Classification from Crowdsourced Labels (AAAI 2025)
• Mingxuan Xia, Zenan Huang, Runze Wu, Gengyu Lyu, Junbo Zhao, Gang Chen, and Haobo Wang. Unbiased Multi-Label Learning from Crowdsourced Annotations (ICML 2024) paper
• Mingxuan Xia, Junbo Zhao, Gengyu Lyu, Zenan Huang, Tianlei Hu, Gang Chen, and Haobo Wang. A Separation and Alignment Framework for Black-Box Domain Adaptation (AAAI 2024) paper
• Haobo Wang, Mingxuan Xia, Yixuan Li, Yuren Mao, Lei Feng, Gang Chen, and Junbo Zhao. Solar: Sinkhorn label refinery for imbalanced partial-label learning (NeurIPS 2022) paper
• Pengyu Xu, Mingxuan Xia, Lin Xiao, Huafeng Liu, Bing Liu, Liping Jing, and Jian Yu. Textual tag recommendation with multi-tag topical attention (Neurocomputing 2023)
• Haomin Wen, Youfang Lin, Yuxuan Hu, Fan Wu, Mingxuan Xia, Xinyi Zhang, Lixia Wu, Haoyuan Hu, and Huaiyu Wan. Modeling Spatial–Temporal Constraints and Spatial-Transfer Patterns for Couriers’ Package Pick-up Route Prediction (TITS 2023)
• Shaokai Wang, Mingxuan Xia, Zilong Wang, Gengyu Lyu, and Songhe Feng. Partial label learning with noisy side information (Applied Intelligence 2022)

Awards

1. National Scholarship, 2023-2024
2. Huawei Scholarship, 2020-2021
3. National Scholarship, 2019-2020
4. National Scholarship, 2018-2019

Experience

• Research Intern in MSRA, Beijing, China (01.2024 - 04.2024)
• Intern in Netease Inc., Hangzhou, China (07.2022 - 09.2022)

Academic Services

• ICLR 2025 reviewer
• ECCV 2024 reviewer