@article{li2025hiddenlifetokensreducing,title={The Hidden Life of Tokens: Reducing Hallucination of Large Vision-Language Models via Visual Information Steering},author={Li, Zhuowei and Shi, Haizhou and Gao, Yunhe and Liu, Di and Wang, Zhenting and Chen, Yuxiao and Liu, Ting and Zhao, Long and Wang, Hao and Metaxas, Dimitris N},journal={arXiv:2502.03628 (pre-print)},year={2025},}
Implicit In-context Learning
Zhuowei Li, Zihao Xu, Ligong Han, Yunhe Gao, Song Wen, Di Liu, Hao Wang, and Dimitris N Metaxas
The Thirteenth International Conference on Learning Representations (ICLR), 2025
@article{li2024implicit,title={Implicit In-context Learning},author={Li, Zhuowei and Xu, Zihao and Han, Ligong and Gao, Yunhe and Wen, Song and Liu, Di and Wang, Hao and Metaxas, Dimitris N},journal={The Thirteenth International Conference on Learning Representations (ICLR)},year={2025},}
2024
MLLM-as-a-Judge for Image Safety without Human Labeling
Zhenting Wang, Shuming Hu, Shiyu Zhao, Xiaowen Lin, Felix Juefei-Xu, Zhuowei Li, Ligong Han, Harihar Subramanyam, Li Chen, Jianfa Chen, and 5 more authors
@article{wang2024mllmasajudgeimagesafetyhuman,title={MLLM-as-a-Judge for Image Safety without Human Labeling},author={Wang, Zhenting and Hu, Shuming and Zhao, Shiyu and Lin, Xiaowen and Juefei-Xu, Felix and Li, Zhuowei and Han, Ligong and Subramanyam, Harihar and Chen, Li and Chen, Jianfa and Jiang, Nan and Lyu, Lingjuan and Ma, Shiqing and Metaxas, Dimitris N. and Jain, Ankit},journal={arXiv:2501.00192 (pre-print)},year={2024},}
Steering prototypes with prompt-tuning for rehearsal-free continual learning
Zhuowei Li, Long Zhao, Zizhao Zhang, Han Zhang, Di Liu, Ting Liu, and Dimitris N Metaxas
In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024
@inproceedings{li2024steering,title={Steering prototypes with prompt-tuning for rehearsal-free continual learning},author={Li, Zhuowei and Zhao, Long and Zhang, Zizhao and Zhang, Han and Liu, Di and Liu, Ting and Metaxas, Dimitris N},booktitle={Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision},pages={2523--2533},year={2024},}
Training Like a Medical Resident: Context-Prior Learning Toward Universal Medical Image Segmentation
Yunhe Gao, Zhuowei Li, Di Liu, Mu Zhou, Shaoting Zhang, and DN Meta
In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024
@inproceedings{Gao_2024_CVPR,author={Gao, Yunhe and Li, Zhuowei and Liu, Di and Zhou, Mu and Zhang, Shaoting and Meta, DN},title={Training Like a Medical Resident: Context-Prior Learning Toward Universal Medical Image Segmentation},booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},year={2024},pages={11194-11204},}
2023
Deformer: Integrating transformers with deformable models for 3d shape abstraction from a single image
Di Liu, Xiang Yu, Meng Ye, Qilong Zhangli, Zhuowei Li, Zhixing Zhang, and Dimitris N Metaxas
In Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023
@inproceedings{liu2023deformer,title={Deformer: Integrating transformers with deformable models for 3d shape abstraction from a single image},author={Liu, Di and Yu, Xiang and Ye, Meng and Zhangli, Qilong and Li, Zhuowei and Zhang, Zhixing and Metaxas, Dimitris N},booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},pages={14236--14246},year={2023},}
2022
Towards self-supervised and weight-preserving neural architecture search
Zhuowei Li, Yibo Gao, Zhenzhou Zha, Zhiqiang Hu, Qing Xia, Shaoting Zhang, and Dimitris N Metaxas
@inproceedings{li2022towards,title={Towards self-supervised and weight-preserving neural architecture search},author={Li, Zhuowei and Gao, Yibo and Zha, Zhenzhou and Hu, Zhiqiang and Xia, Qing and Zhang, Shaoting and Metaxas, Dimitris N},booktitle={European Conference on Computer Vision},pages={3--19},year={2022},organization={Springer},}
Contrastive and selective hidden embeddings for medical image segmentation
@article{liu2022contrastive,title={Contrastive and selective hidden embeddings for medical image segmentation},author={Liu, Zihao and Li, Zhuowei and Hu, Zhiqiang and Xia, Qing and Xiong, Ruiqin and Zhang, Shaoting and Jiang, Tingting},journal={IEEE Transactions on Medical Imaging},volume={41},number={11},pages={3398--3410},year={2022},publisher={IEEE},}
2021
A deep reinforced tree-traversal agent for coronary artery centerline extraction
In Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th International Conference, Strasbourg, France, September 27–October 1, 2021, Proceedings, Part V 24, 2021
@inproceedings{li2021deep,title={A deep reinforced tree-traversal agent for coronary artery centerline extraction},author={Li, Zhuowei and Xia, Qing and Hu, Zhiqiang and Wang, Wenji and Xu, Lijian and Zhang, Shaoting},booktitle={Medical Image Computing and Computer Assisted Intervention--MICCAI 2021: 24th International Conference, Strasbourg, France, September 27--October 1, 2021, Proceedings, Part V 24},pages={418--428},year={2021},organization={Springer},}
Self-ensembling contrastive learning for semi-supervised medical image segmentation
@article{xiang2021self,title={Self-ensembling contrastive learning for semi-supervised medical image segmentation},author={Xiang, Jinxi and Li, Zhuowei and Wang, Wenji and Xia, Qing and Zhang, Shaoting},journal={arXiv preprint arXiv:2105.12924},year={2021},}
Few-shot learning by a cascaded framework with shape-constrained pseudo label assessment for whole heart segmentation
Wenji Wang, Qing Xia, Zhiqiang Hu, Zhennan Yan, Zhuowei Li, Yang Wu, Ning Huang, Yue Gao, Dimitris Metaxas, and Shaoting Zhang
@article{wang2021few,title={Few-shot learning by a cascaded framework with shape-constrained pseudo label assessment for whole heart segmentation},author={Wang, Wenji and Xia, Qing and Hu, Zhiqiang and Yan, Zhennan and Li, Zhuowei and Wu, Yang and Huang, Ning and Gao, Yue and Metaxas, Dimitris and Zhang, Shaoting},journal={IEEE Transactions on Medical Imaging},volume={40},number={10},pages={2629--2641},year={2021},publisher={IEEE},}
2020
Segmentation to label: automatic coronary artery labeling from mask parcellation
In Machine Learning in Medical Imaging: 11th International Workshop, MLMI 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4, 2020, Proceedings 11, 2020
@inproceedings{li2020segmentation,title={Segmentation to label: automatic coronary artery labeling from mask parcellation},author={Li, Zhuowei and Xia, Qing and Wang, Wenji and Yan, Zhennan and Yin, Ruohan and Pan, Changjie and Metaxas, Dimitris},booktitle={Machine Learning in Medical Imaging: 11th International Workshop, MLMI 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4, 2020, Proceedings 11},pages={130--138},year={2020},organization={Springer},}
2019
One-shot learning for function-specific region segmentation in mouse brain
Xu Zhang, Zhuowei Li*, Pei-Jie Wang, Katelyn Y Liao, Shen-Ju Chou, Shih-Fu Chang, and Jung-Chi Liao
In 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019), 2019
@inproceedings{zhang2019one,title={One-shot learning for function-specific region segmentation in mouse brain},author={Zhang, Xu and Li, Zhuowei and Wang, Pei-Jie and Liao, Katelyn Y and Chou, Shen-Ju and Chang, Shih-Fu and Liao, Jung-Chi},booktitle={2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019)},pages={736--740},year={2019},organization={IEEE},}
