Lijun Sheng

According to our database, Lijun Sheng authored at least 24 papers between 2023 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Do MLLMs Really Understand Space? A Mathematical Reasoning Evaluation.

Shuo Lu, Jianjie Cheng, Yinuo Xu, Yongcan Yu, Lijun Sheng, Peijie Wang, Siru Jiang, Yongguan Hu, Run Ling, Yihua Shao, Ao Ma, Wei Feng, Lingxiao He, Meng Wang, Qianlong Xie, Xingxing Wang, Ran He, Jian Liang

CoRR, February, 2026

Out-of-Distribution Detection: A Task-Oriented Survey of Recent Advances.

Shuo Lu, Yingsheng Wang, Lijun Sheng, Lingxiao He, Aihua Zheng, Jian Liang

ACM Comput. Surv., January, 2026

Learning Fair Domain Adaptation with Virtual Label Distribution.

Yuguang Zhang, Lijun Sheng, Jian Liang, Ran He

CoRR, January, 2026

Harmonizing class uniformity and separability for transferability estimation.

Yuhe Ding, Bo Jiang, Lijun Sheng, Aihua Zheng, Jian Liang

Pattern Recognit., 2026

2025

Reassessing the Role of Supervised Fine-Tuning: An Empirical Study in VLM Reasoning.

Yongcan Yu, Lingxiao He, Shuo Lu, Lijun Sheng, Yinuo Xu, Yanbo Wang, Kuangpu Guo, Jianjie Cheng, Meng Wang, Qianlong Xie, Xingxing Wang, Dapeng Hu, Jian Liang

CoRR, December, 2025

Adapting Vision-Language Models Without Labels: A Comprehensive Survey.

Hao Dong, Lijun Sheng, Jian Liang, Ran He, Eleni N. Chatzi, Olga Fink

CoRR, August, 2025

The Illusion of Progress? A Critical Look at Test-Time Adaptation for Vision-Language Models.

Lijun Sheng, Jian Liang, Ran He, Zilei Wang, Tieniu Tan

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Cooperative Pseudo Labeling for Unsupervised Federated Classification.

Kuangpu Guo, Lijun Sheng, Yongcan Yu, Jian Liang, Zilei Wang, Ran He

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2025

R-TPT: Improving Adversarial Robustness of Vision-Language Models through Test-Time Prompt Tuning.

Lijun Sheng, Jian Liang, Zilei Wang, Ran He

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

Protecting Model Adaptation from Trojans in the Unlabeled Data.

Lijun Sheng, Jian Liang, Ran He, Zilei Wang, Tieniu Tan

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

Learning Spatiotemporal Inconsistency via Thumbnail Layout for Face Deepfake Detection.

Yuting Xu, Jian Liang, Lijun Sheng, Xiaoyu Zhang

Int. J. Comput. Vis., December, 2024

Towards Compatible Fine-tuning for Vision-Language Model Updates.

Zhengbo Wang, Jian Liang, Lijun Sheng, Ran He, Zilei Wang, Tieniu Tan

CoRR, 2024

Prototypical Distillation and Debiased Tuning for Black-box Unsupervised Domain Adaptation.

Jian Liang, Lijun Sheng, Hongmin Liu, Ran He

CoRR, 2024

Recent Advances in OOD Detection: Problems and Approaches.

Shuo Lu, Yingsheng Wang, Lijun Sheng, Aihua Zheng, Lingxiao He, Jian Liang

CoRR, 2024

Can We Trust the Unlabeled Target Data? Towards Backdoor Attack and Defense on Model Adaptation.

Lijun Sheng, Jian Liang, Ran He, Zilei Wang, Tieniu Tan

CoRR, 2024

Realistic Unsupervised CLIP Fine-tuning with Universal Entropy Optimization.

Jian Liang, Lijun Sheng, Zhengbo Wang, Ran He, Tieniu Tan

Proceedings of the Forty-first International Conference on Machine Learning, 2024

A Hard-to-Beat Baseline for Training-free CLIP-based Adaptation.

Zhengbo Wang, Jian Liang, Lijun Sheng, Ran He, Zilei Wang, Tieniu Tan

Proceedings of the Twelfth International Conference on Learning Representations, 2024

STAMP: Outlier-Aware Test-Time Adaptation with Stable Memory Replay.

Yongcan Yu, Lijun Sheng, Ran He, Jian Liang

Proceedings of the Computer Vision - ECCV 2024, 2024

2023

ProxyMix: Proxy-based Mixup training with label refinery for source-free domain adaptation.

Yuhe Ding, Lijun Sheng, Jian Liang, Aihua Zheng, Ran He

Neural Networks, October, 2023

Self-training solutions for the ICCV 2023 GeoNet Challenge.

Lijun Sheng, Zhengbo Wang, Jian Liang

CoRR, 2023

Unleashing the power of Neural Collapse for Transferability Estimation.

Yuhe Ding, Bo Jiang, Lijun Sheng, Aihua Zheng, Jian Liang

CoRR, 2023

Towards Realistic Unsupervised Fine-tuning with CLIP.

Jian Liang, Lijun Sheng, Zhengbo Wang, Ran He, Tieniu Tan

CoRR, 2023

Benchmarking Test-Time Adaptation against Distribution Shifts in Image Classification.

Yongcan Yu, Lijun Sheng, Ran He, Jian Liang

CoRR, 2023

AdaptGuard: Defending Against Universal Attacks for Model Adaptation.

Lijun Sheng, Jian Liang, Ran He, Zilei Wang, Tieniu Tan

CoRR, 2023