Lin Li

According to our database, Lin Li authored at least 16 papers between 2023 and 2026.

Collaborative distances:

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

2026

MEDSYN: Benchmarking Multi-EviDence SYNthesis in Complex Clinical Cases for Multimodal Large Language Models.

Boqi Chen, Xudong Liu, Jiachuan Peng, Marianne Frey-Marti, Bang Zheng, Kyle Lam, Lin Li, Jianing Qiu

CoRR, February, 2026

2025

Towards Robust Protective Perturbation against DeepFake Face Swapping.

Hengyang Yao, Lin Li, Ke Sun, Jianing Qiu, Huiping Chen

CoRR, December, 2025

Emerging Cyber Attack Risks of Medical AI Agents.

Jianing Qiu, Lin Li, Jiankai Sun, Hao Wei, Zhe Xu, Kyle Lam, Wu Yuan

CoRR, April, 2025

AROID: Improving Adversarial Robustness Through Online Instance-Wise Data Augmentation.

Lin Li, Jianing Qiu, Michael W. Spratling

Int. J. Comput. Vis., February, 2025

Robust shortcut and disordered robustness: Improving adversarial training through adaptive smoothing.

Lin Li, Michael W. Spratling

Pattern Recognit., 2025

Advancing robots with greater dynamic dexterity: A large-scale multi-view and multi-modal dataset of human-human throw&catch of arbitrary objects.

Lipeng Chen, Jianing Qiu, Lin Li, Xi Luo, Guoyi Chi, Yu Zheng

Int. J. Robotics Res., 2025

2024

Artificial Intelligence for Biomedical Video Generation.

Linyuan Li, Jianing Qiu, Anujit Saha, Lin Li, Poyuan Li, Mengxian He, Ziyu Guo, Wu Yuan

CoRR, 2024

OODRobustBench: a Benchmark and Large-Scale Analysis of Adversarial Robustness under Distribution Shift.

Lin Li, Yifei Wang, Chawin Sitawarin, Michael W. Spratling

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

One Prompt Word is Enough to Boost Adversarial Robustness for Pre-Trained Vision-Language Models.

Lin Li, Haoyan Guan, Jianing Qiu, Michael W. Spratling

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Large AI Models in Health Informatics: Applications, Challenges, and the Future.

Jianing Qiu, Lin Li, Jiankai Sun, Jiachuan Peng, Peilun Shi, Ruiyang Zhang, Yinzhao Dong, Kyle Lam, Frank P.-W. Lo, Bo Xiao, Wu Yuan, Ningli Wang, Dong Xu, Benny P. L. Lo

IEEE J. Biomed. Health Informatics, December, 2023

Understanding and combating robust overfitting via input loss landscape analysis and regularization.

Lin Li, Michael W. Spratling

Pattern Recognit., April, 2023

OODRobustBench: benchmarking and analyzing adversarial robustness under distribution shift.

Lin Li, Yifei Wang, Chawin Sitawarin, Michael W. Spratling

CoRR, 2023

VisionFM: a Multi-Modal Multi-Task Vision Foundation Model for Generalist Ophthalmic Artificial Intelligence.

Jianing Qiu, Jian Wu, Hao Wei, Peilun Shi, Minqing Zhang, Yunyun Sun, Lin Li, Hanruo Liu, Hongyi Liu, Simeng Hou, Yuyang Zhao, Xuehui Shi, Junfang Xian, Xiaoxia Qu, Sirui Zhu, Lijie Pan, Xiaoniao Chen, Xiaojia Zhang, Shuai Jiang, Kebing Wang, Chenlong Yang, Mingqiang Chen, Sujie Fan, Jianhua Hu, Aiguo Lv, Hui Miao, Li Guo, Shujun Zhang, Cheng Pei, Xiaojuan Fan, Jianqin Lei, Ting Wei, Junguo Duan, Chun Liu, Xiaobo Xia, Siqi Xiong, Junhong Li, Benny Lo, Yih Chung Tham, Tien Yin Wong, Ningli Wang, Wu Yuan

CoRR, 2023

Improved Adversarial Training Through Adaptive Instance-wise Loss Smoothing.

Lin Li, Michael W. Spratling

CoRR, 2023

Large AI Models in Health Informatics: Applications, Challenges, and the Future.

Jianing Qiu, Lin Li, Jiankai Sun, Jiachuan Peng, Peilun Shi, Ruiyang Zhang, Yinzhao Dong, Kyle Lam, Frank P.-W. Lo, Bo Xiao, Wu Yuan, Dong Xu, Benny Lo

CoRR, 2023

Data augmentation alone can improve adversarial training.

Lin Li, Michael W. Spratling

Proceedings of the Eleventh International Conference on Learning Representations, 2023