AdaptGuard: Defending Against Universal Attacks for Model Adaptation. - Lijun Sheng; Jian Liang 001; Ran He 001; Zilei Wang; Tieniu Tan (CoRR, 2023)

Benchmarking Test-Time Adaptation against Distribution Shifts in Image Classification. - Yongcan Yu; Lijun Sheng; Ran He 001; Jian Liang 001 (CoRR, 2023)

Towards Realistic Unsupervised Fine-tuning with CLIP. - Jian Liang 001; Lijun Sheng; Zhengbo Wang; Ran He 001; Tieniu Tan (CoRR, 2023)

Unleashing the power of Neural Collapse for Transferability Estimation. - Yuhe Ding; Bo Jiang 002; Lijun Sheng; Aihua Zheng; Jian Liang 001 (CoRR, 2023)

Self-training solutions for the ICCV 2023 GeoNet Challenge. - Lijun Sheng; Zhengbo Wang; Jian Liang 001 (CoRR, 2023)

ProxyMix: Proxy-based Mixup training with label refinery for source-free domain adaptation. - Yuhe Ding; Lijun Sheng; Jian Liang 001; Aihua Zheng; Ran He 001 (Neural Networks, 2023)

STAMP: Outlier-Aware Test-Time Adaptation with Stable Memory Replay. - Yongcan Yu; Lijun Sheng; Ran He 001; Jian Liang 001 (ECCV (81), 2024)

A Hard-to-Beat Baseline for Training-free CLIP-based Adaptation. - Zhengbo Wang; Jian Liang 001; Lijun Sheng; Ran He 001; Zilei Wang; Tieniu Tan (ICLR, 2024)

Realistic Unsupervised CLIP Fine-tuning with Universal Entropy Optimization. - Jian Liang 001; Lijun Sheng; Zhengbo Wang; Ran He 001; Tieniu Tan (ICML, 2024)

Can We Trust the Unlabeled Target Data? Towards Backdoor Attack and Defense on Model Adaptation. - Lijun Sheng; Jian Liang 001; Ran He 001; Zilei Wang; Tieniu Tan (CoRR, 2024)

Recent Advances in OOD Detection: Problems and Approaches. - Shuo Lu; Yingsheng Wang; Lijun Sheng; Aihua Zheng; Lingxiao He; Jian Liang 001 (CoRR, 2024)

Prototypical Distillation and Debiased Tuning for Black-box Unsupervised Domain Adaptation. - Jian Liang 001; Lijun Sheng; Hongmin Liu; Ran He 001 (CoRR, 2024)

Towards Compatible Fine-tuning for Vision-Language Model Updates. - Zhengbo Wang; Jian Liang 001; Lijun Sheng; Ran He 001; Zilei Wang; Tieniu Tan (CoRR, 2024)

Learning Spatiotemporal Inconsistency via Thumbnail Layout for Face Deepfake Detection. - Yuting Xu; Jian Liang 001; Lijun Sheng; Xiaoyu Zhang 002 (Int. J. Comput. Vis., 2024)

Protecting Model Adaptation from Trojans in the Unlabeled Data. - Lijun Sheng; Jian Liang 001; Ran He 001; Zilei Wang; Tieniu Tan (AAAI, 2025)

R-TPT: Improving Adversarial Robustness of Vision-Language Models through Test-Time Prompt Tuning. - Lijun Sheng; Jian Liang 001; Zilei Wang; Ran He 001 (CVPR, 2025)

The Illusion of Progress? A Critical Look at Test-Time Adaptation for Vision-Language Models. - Lijun Sheng; Jian Liang 001; Ran He 001; Zilei Wang; Tieniu Tan (CoRR, 2025)

Adapting Vision-Language Models Without Labels: A Comprehensive Survey. - Hao Dong; Lijun Sheng; Jian Liang; Ran He; Eleni N. Chatzi; Olga Fink (CoRR, 2025)