侍蒋鑫 Jiang-Xin Shi Ph.D. Student LAMDA Group School of Artificial Intelligence National Key Laboratory for Novel Software Technology Nanjing University, Nanjing 210023, China Supervisor: Professor Yu-Feng Li Email: shijx@lamda.nju.edu.cn [Google Scholar] [DBLP] [GitHub]

Biography

Currently, I am pursuing my Ph.D. degree at the School of Artificial Intelligence, Nanjing University. I am also a member of LAMDA Group, which is led by Professor Zhi-Hua Zhou.

• 2023.09 - Now: Ph.D. Student, LAMDA Group & School of Artificial Intelligence, Nanjing University.

• 2020.09 - 2023.06: Graduate Student, LAMDA Group & Department of Computer Science and Technology, Nanjing University.

• 2016.09 - 2020.06: Undergraduate Student, School of Computer Science, Northwestern Polytechnical University.

Research Interests

My research interests include Machine Learning and Data Mining.

• Particularly, I am interested in Long-Tail Learning (studying how to learn from data with long-tail distributions). Here is a wonderful repository maintained by Dr. Tong Wei: [Awesome Long-Tail Learning].

Publications (* denotes equal contribution)

Conference Papers

• Vision-Language Models are Strong Noisy Label Detectors. [pdf] [code]
  Tong Wei, Hao-Tian Li, Chun-Shu Li, Jiang-Xin Shi, Yu-Feng Li, Min-Ling Zhang.
  In: Advances in Neural Information Processing Systems 37 (NeurIPS 2024).

• Efficient and Long-Tailed Generalization for Pre-trained Vision-Language Model. [pdf] [code]
  Jiang-Xin Shi*, Chi Zhang*, Tong Wei, Yu-Feng Li.
  In: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024).

• Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts. [pdf] [code]
  Jiang-Xin Shi*, Tong Wei*, Zhi Zhou, Jie-Jing Shao, Xin-Yan Han, Yu-Feng Li.
  In: Proceedings of the 41st International Conference on Machine Learning (ICML 2024).

• DeCoOp: Robust Prompt Tuning with Out-of-Distribution Detection. [pdf] [code]
  Zhi Zhou, Ming Yang, Jiang-Xin Shi, Lan-Zhe Guo, Yu-Feng Li.
  In: Proceedings of the 41st International Conference on Machine Learning (ICML 2024).

• How Re-sampling Helps for Long-Tail Learning? [pdf] [code]
  Jiang-Xin Shi*, Tong Wei*, Yuke Xiang, Yu-Feng Li.
  In: Advances in Neural Information Processing Systems 36 (NeurIPS 2023).

• Prototypical Classifier for Robust Class-Imbalanced Learning. [pdf] [code]
  Tong Wei*, Jiang-Xin Shi*, Yu-Feng Li, Min-Ling Zhang.
  In: Advances in Knowledge Discovery and Data Mining (PAKDD 2022).
  (PAKDD 2022 Best Paper Award)

• Probabilistic Label Tree for Streaming Multi-Label Learning. [pdf] [code]
  Tong Wei*, Jiang-Xin Shi*, Yu-Feng Li.
  In: Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2021).

Journal Papers

• Robust Long-Tailed Learning under Label Noise. [arxiv] [code]
  Tong Wei*, Jiang-Xin Shi*, Min-Ling Zhang, Yu-Feng Li.
  Frontiers of Computer Science (FCS), In Press.

• Residual Diverse Ensemble for Long-Tailed Multi-Label Text Classification. [pdf] [code]
  Jiang-Xin Shi*, Tong Wei*, Yu-Feng Li.
  SCIENCE CHINA Information Sciences (SCIS), 2024.

• Transfer and Share: Semi-Supervised Learning from Long-Tailed Data. [pdf] [code]
  Tong Wei*, Qian-Yu Liu*, Jiang-Xin Shi, Wei-Wei Tu, Lan-Zhe Guo.
  Machine Learning (MLJ), 2022.

Other Papers

• LIFT+: Lightweight Fine-Tuning for Long-Tail Learning. [arxiv] [code]
  Jiang-Xin Shi, Tong Wei, Yu-Feng Li.
  arXiv:2504.13282, 2025.

• LawGPT: A Chinese Legal Knowledge-Enhanced Large Language Model. [arxiv]
  Zhi Zhou*, Jiang-Xin Shi*, Peng-Xiao Song*, Xiao-Wen Yang*, Yi-Xuan Jin, Lan-Zhe Guo, Yu-Feng Li.
  arXiv:2406.04614, 2024.

• Investigating the Limitation of CLIP Models: The Worst-Performing Categories. [arxiv]
  Jie-Jing Shao*, Jiang-Xin Shi*, Xiao-Wen Yang*, Lan-Zhe Guo, Yu-Feng Li.
  arXiv:2310.03324, 2023.

• A Survey on Extreme Multi-label Learning. [arxiv]
  Tong Wei, Zhen Mao, Jiang-Xin Shi, Yu-Feng Li, Min-Ling Zhang.
  arXiv:2210.03968, 2022.

Awards & Honors

• 南京大学博士生英才奖学金一等奖, 2023.

• PAKDD Best Paper Award, 2022.

• Outstanding Graduate of Northwestern Polytechnical University, 2020.

• CCF Elite Collegiate Award, 2019.

• ACM-ICPC Asia Regional Contest Gold Medal, 2018 and 2017.

• National Scholarship, 2018 and 2017.

Services

• SPC Member for: IJCAI 2025.

• PC Member for: ICML 2023, 2024, 2025; NeurIPS 2023, 2024, 2025; ICLR 2024, 2025; KDD 2024; AAAI 2023, 2024, 2025; ICCV 2025; ACML 2022, 2024, 2025; ECAI 2023; AISTATS 2025; PRCV 2024.

• Journal Reviewer for: Machine Learning; Frontiers of Computer Science; IET Computer Vision.

• Captain of Northwestern Polytechnical University ACM-ICPC Competition Team, 2018.

Teaching Assistant

• Matrix Computation, Nanjing Univeristy, Spring, 2025.

• Introduction to Advanced Machine Learning, Nanjing Univeristy, Spring, 2022.

• Introduction to Machine Learning, Nanjing Univeristy, Fall, 2021.

Correspondence

Email: shijx@lamda.nju.edu.cn

Office: Room A515, Yifu Building, Xianlin Campus

Address: 163 Xianlin Avenue, Qixia District, Nanjing 210023, China