| 2025 | CVPR | Enhancing Privacy-Utility Trade-offs to Mitigate Memorization in Diffusion Models. | Chen Chen, Daochang Liu, Mubarak Shah, Chang Xu |
| 2025 | ICLR | Exploring Local Memorization in Diffusion Models via Bright Ending Attention. | Chen Chen, Daochang Liu, Mubarak Shah, Chang Xu |
| 2025 | ICLR | Representative Guidance: Diffusion Model Sampling with Coherence. | Anh-Dung Dinh, Daochang Liu, Chang Xu |
| 2025 | ICLR | Anti-Exposure Bias in Diffusion Models. | Junyu Zhang, Daochang Liu, Eunbyung Park, Shichao Zhang, Chang Xu |
| 2025 | MICCAI | DentEval: Fine-tuning-Free Expert-Aligned Assessment in Dental Education via LLM Agents. | Xinyu Deng, Vesna Miletic, Elvis Trinh, Jinlong Gao, Chang Xu, Daochang Liu |
| 2025 | NAACL | CollagePrompt: A Benchmark for Budget-Friendly Visual Recognition with GPT-4V. | Siyu Xu, Yunke Wang, Daochang Liu, Bo Du, Chang Xu |
| 2025 | WWW | Workshop on Sustainable AI for the Future Web. | Chang Xu, Yunke Wang, Jianyuan Guo, Daochang Liu, Minjing Dong, Yasmeen M. George, Johan Barthelemy, Yan Liu, Ling Chen |
| 2024 | CVPR | Towards Memorization-Free Diffusion Models. | Chen Chen, Daochang Liu, Chang Xu |
| 2024 | CVPR | Residual Learning in Diffusion Models. | Junyu Zhang, Daochang Liu, Eunbyung Park, Shichao Zhang, Chang Xu |
| 2024 | ICML | Bridging Data Gaps in Diffusion Models with Adversarial Noise-Based Transfer Learning. | Xiyu Wang, Baijiong Lin, Daochang Liu, Ying-Cong Chen, Chang Xu |
| 2024 | IJCAI | Boosting Diffusion Models with an Adaptive Momentum Sampler. | Xiyu Wang, Anh-Dung Dinh, Daochang Liu, Chang Xu |
| 2023 | CVPR | Private Image Generation with Dual-Purpose Auxiliary Classifier. | Chen Chen, Daochang Liu, Siqi Ma, Surya Nepal, Chang Xu |
| 2023 | ICCV | Personalized Image Generation for Color Vision Deficiency Population. | Shuyi Jiang, Daochang Liu, Dingquan Li, Chang Xu |
| 2023 | ICCV | Diffusion Action Segmentation. | Daochang Liu, Qiyue Li, Anh-Dung Dinh, Tingting Jiang, Mubarak Shah, Chang Xu |
| 2023 | ICML | PixelAsParam: A Gradient View on Diffusion Sampling with Guidance. | AnhDung Dinh, Daochang Liu, Chang Xu |
| 2023 | IJCAI | Calibrating a Deep Neural Network with Its Predecessors. | Linwei Tao, Minjing Dong, Daochang Liu, Changming Sun, Chang Xu |
| 2022 | ICDM | Contrastive Code-Comment Pre-training. | Xiaohuan Pei, Daochang Liu, Luo Qian, Chang Xu |
| 2021 | CVPR | Towards Unified Surgical Skill Assessment. | Daochang Liu, Qiyue Li, Tingting Jiang, Yizhou Wang, Rulin Miao, Fei Shan, Ziyu Li |
| 2020 | MICCAI | Unsupervised Surgical Instrument Segmentation via Anchor Generation and Semantic Diffusion. | Daochang Liu, Yuhui Wei, Tingting Jiang, Yizhou Wang, Rulin Miao, Fei Shan, Ziyu Li |
| 2019 | CVPR | Completeness Modeling and Context Separation for Weakly Supervised Temporal Action Localization. | Daochang Liu, Tingting Jiang, Yizhou Wang |
| 2019 | MICCAI | Surgical Skill Assessment on In-Vivo Clinical Data via the Clearness of Operating Field. | Daochang Liu, Tingting Jiang, Yizhou Wang, Rulin Miao, Fei Shan, Ziyu Li |
| 2018 | MICCAI | Deep Reinforcement Learning for Surgical Gesture Segmentation and Classification. | Daochang Liu, Tingting Jiang |