| Adversarial Example Does Good: Preventing Painting Imitation from Diffusion Models via Adversarial Examples C Liang, X Wu, Y Hua, J Zhang, Y Xue, T Song, Z Xue, R Ma, H Guan International Conference on Machine Learning, 20763-20786, 2023 | 96 | 2023 |
| Mist: Towards improved adversarial examples for diffusion models C Liang, X Wu arXiv preprint arXiv:2305.12683, 2023 | 33 | 2023 |
| Targeted Attack Improves Protection against Unauthorized Diffusion Customization B Zheng, C Liang, X Wu arXiv preprint arXiv:2310.04687, 2023 | 19* | 2023 |
| Toward effective protection against diffusion-based mimicry through score distillation H Xue, C Liang, X Wu, Y Chen The Twelfth International Conference on Learning Representations, 2023 | 17 | 2023 |
| Cblab: Supporting the training of large-scale traffic control policies with scalable traffic simulation C Liang, Z Huang, Y Liu, Z Liu, G Zheng, H Shi, K Wu, Y Du, F Li, ZJ Li Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 15* | 2023 |
| Fdti: Fine-grained deep traffic inference with roadnet-enriched graph Z Liu, C Liang, G Zheng, H Wei Joint European Conference on Machine Learning and Knowledge Discovery in …, 2023 | 6 | 2023 |
| Cgi-dm: Digital copyright authentication for diffusion models via contrasting gradient inversion X Wu, Y Hua, C Liang, J Zhang, H Wang, T Song, H Guan 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR …, 2024 | 3 | 2024 |
| Real-World Benchmarks Make Membership Inference Attacks Fail on Diffusion Models C Liang, J You arXiv preprint arXiv:2410.03640, 2024 | | 2024 |
| MOTSC: Model-based Offline Traffic Signal Control Y Liu, C Liang, Z Huang, G Zheng | | |
Xiaoyu WuShanghai Jiao Tong UniversityVerified email at sjtu.edu.cn
