Lijun Sheng (生力军)

tom.jpg

I am currently a Ph.D. student in University of Science and Technology of China, supervised by Prof. Tieniu Tan and jointly supervised by Prof. Jian Liang, Prof. Ran He and Prof. Zilei Wang. Before that, I received bachelor’s degree in Automation in University of Science and Technology of China in 2020.

My research interests are unsupervised learning during test time, trustworthy machine learning, and visual language models.

news

Sep 19, 2025 A paper is accepted by NeurIPS 2025 (D&B Track).
Feb 27, 2025 A paper is accepted by CVPR 2025.
Dec 10, 2024 A paper is accepted by AAAI 2025.
Sep 30, 2023 Going to Paris to attend ICCV 2023 !
Jul 14, 2023 A paper is accepted by ICCV 2023.

publications

  1. ICCV
    AdaptGuard: Defending Against Universal Attacks for Model Adaptation
    Lijun Sheng, Jian Liang, Ran He, Zilei Wang, and Tieniu Tan
    In International Conference on Computer Vision (ICCV) , 2023
  2. AAAI
    Protecting Model Adaptation from Trojans in the Unlabeled Data
    Lijun Sheng, Jian Liang, Ran He, Zilei Wang, and Tieniu Tan
    In AAAI Conference on Artificial Intelligence (AAAI) , 2025
  3. CVPR
    R-TPT: Improving Adversarial Robustness of Vision-Language Models through Test-Time Prompt Tuning
    Lijun Sheng, Jian Liang, Zilei Wang, and Ran He
    In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , 2025
  4. NeurIPS
    The Illusion of Progress? A Critical Look at Test-Time Adaptation for Vision-Language Models
    Lijun Sheng, Jian Liang, Ran He, Zilei Wang, and Tieniu Tan
    In NeurIPS Datasets and Benchmarks Track , 2025
  5. Adapting Vision-Language Models Without Labels: A Comprehensive Survey
    Hao Dong, Lijun Sheng, Jian Liang, Ran He, Eleni Chatzi, and Olga Fink
    arXiv preprint arXiv:2508.05547, 2025
  6. ICML
    Realistic Unsupervised CLIP Fine-tuning with Universal Entropy Optimization
    Jian Liang, Lijun Sheng, Zhengbo Wang, Ran He, and Tieniu Tan
    In International Conference on Machine Learning (ICML), Spotlight , 2024
  7. NN
    ProxyMix: Proxy-based Mixup Training with Label Refinery for Source-Free Domain Adaptation
    Yuhe Ding, Lijun Sheng, Jian Liang, Aihua Zheng, and Ran He
    Neural Networks, 2023