@article{zhu2026simple,title={A Simple Baseline for Unifying Understanding, Generation, and Editing via Vanilla Next-token Prediction},author={Zhu, Jie and Ma, Hanghang and Wang, Jia and Guan, Yayong and Zeng, Yanbing and Gao, Lishuai and Wu, Junqiang and Hu, Jie and Wang, Leye},journal={arXiv preprint arXiv:2603.04980},year={2026},}
2025
Arxiv
A Unified and Scalable Membership Inference Method for Visual Self-supervised Encoder via Part-aware Capability
@article{zhu2025unified,title={A Unified and Scalable Membership Inference Method for Visual Self-supervised Encoder via Part-aware Capability},author={Zhu, Jie and Zha, Jirong and Li, Ding and Wang, Leye},journal={arXiv preprint arXiv:2505.10351},year={2025},}
Arxiv
Auditing Data Provenance in Real-world Text-to-Image Diffusion Models for Privacy and Copyright Protection
@article{zhu2025auditing,title={Auditing Data Provenance in Real-world Text-to-Image Diffusion Models for Privacy and Copyright Protection},author={Zhu, Jie and Wang, Leye},journal={arXiv preprint arXiv:2506.11434},year={2025},}
2024
NeurIPS
Mole: Enhancing human-centric text-to-image diffusion via mixture of low-rank experts
Jie Zhu, Yixiong Chen, Mingyu Ding, Ping Luo, Leye Wang, and Jingdong Wang
Advances in Neural Information Processing Systems, 2024
@article{zhu2024mole,title={Mole: Enhancing human-centric text-to-image diffusion via mixture of low-rank experts},author={Zhu, Jie and Chen, Yixiong and Ding, Mingyu and Luo, Ping and Wang, Leye and Wang, Jingdong},journal={Advances in Neural Information Processing Systems},volume={37},pages={29354--29386},year={2024},}
ACM CCS
A unified membership inference method for visual self-supervised encoder via part-aware capability
Jie Zhu, Jirong Zha, Ding Li, and Leye Wang
In Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security, 2024
@inproceedings{zhu2024unified,title={A unified membership inference method for visual self-supervised encoder via part-aware capability},author={Zhu, Jie and Zha, Jirong and Li, Ding and Wang, Leye},booktitle={Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security},pages={1241--1255},year={2024},}
IEEE TSE
Safety and performance, why not both? bi-objective optimized model compression against heterogeneous attacks toward ai software deployment
Jie Zhu, Leye Wang, Xiao Han, Anmin Liu, and Tao Xie
@article{zhu2024safety,title={Safety and performance, why not both? bi-objective optimized model compression against heterogeneous attacks toward ai software deployment},author={Zhu, Jie and Wang, Leye and Han, Xiao and Liu, Anmin and Xie, Tao},journal={IEEE Transactions on Software Engineering},volume={50},number={3},pages={376--390},year={2024},publisher={IEEE},}
2023
TMLR
Understanding Self-Supervised Pretraining with Part-Aware Representation Learning
Jie Zhu, Jiyang Qi, Mingyu Ding, Xiaokang Chen, Ping Luo, Xinggang Wang, and 3 more authors
@article{zhuunderstanding,title={Understanding Self-Supervised Pretraining with Part-Aware Representation Learning},author={Zhu, Jie and Qi, Jiyang and Ding, Mingyu and Chen, Xiaokang and Luo, Ping and Wang, Xinggang and Liu, Wenyu and Wang, Leye and Wang, Jingdong},journal={Transactions on Machine Learning Research},year={2023},}
ICLR
E-CRF: Embedded Conditional Random Field for Boundary-caused Class Weights Confusion in Semantic Segmentation
Jie Zhu, Huabin Huang, Banghuai Li, and Leye Wang
In The Eleventh International Conference on Learning Representations, 2023
@inproceedings{zhucrf,title={E-CRF: Embedded Conditional Random Field for Boundary-caused Class Weights Confusion in Semantic Segmentation},author={Zhu, Jie and Huang, Huabin and Li, Banghuai and Wang, Leye},booktitle={The Eleventh International Conference on Learning Representations},year={2023},}
2022
ASE
Safety and performance, why not both? bi-objective optimized model compression toward ai software deployment
Jie Zhu, Leye Wang, and Xiao Han
In Proceedings of the 37th IEEE/ACM international conference on automated software engineering, 2022
@inproceedings{zhu2022safety,title={Safety and performance, why not both? bi-objective optimized model compression toward ai software deployment},author={Zhu, Jie and Wang, Leye and Han, Xiao},booktitle={Proceedings of the 37th IEEE/ACM international conference on automated software engineering},pages={1--13},year={2022},}