| Long-tailed recognition by routing diverse distribution-aware experts X Wang, L Lian, Z Miao, Z Liu, SX Yu arXiv preprint arXiv:2010.01809, 2020 | 371 | 2020 |
| Llm-grounded diffusion: Enhancing prompt understanding of text-to-image diffusion models with large language models L Lian, B Li, A Yala, T Darrell arXiv preprint arXiv:2305.13655, 2023 | 89* | 2023 |
| Debiased learning from naturally imbalanced pseudo-labels X Wang, Z Wu, L Lian, SX Yu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 78 | 2022 |
| Q-diffusion: Quantizing diffusion models X Li, Y Liu, L Lian, H Yang, Z Dong, D Kang, S Zhang, K Keutzer Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 67 | 2023 |
| Unsupervised selective labeling for more effective semi-supervised learning X Wang, L Lian, SX Yu European Conference on Computer Vision, 427-445, 2022 | 29 | 2022 |
| Unsupervised visual attention and invariance for reinforcement learning X Wang, L Lian, SX Yu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 29 | 2021 |
| Self-correcting llm-controlled diffusion models TH Wu, L Lian, JE Gonzalez, B Li, T Darrell Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 8 | 2024 |
| Unsupervised universal image segmentation D Niu, X Wang, X Han, L Lian, R Herzig, T Darrell Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 6 | 2024 |
| Bootstrapping objectness from videos by relaxed common fate and visual grouping L Lian, Z Wu, SX Yu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 5 | 2023 |
| Rethinking Patch Dependence for Masked Autoencoders L Fu, L Lian, R Wang, B Shi, X Wang, A Yala, T Darrell, AA Efros, ... arXiv preprint arXiv:2401.14391, 2024 | 3 | 2024 |
| Improving Unsupervised Video Object Segmentation with Motion-Appearance Synergy L Lian, Z Wu, SX Yu arXiv preprint arXiv:2212.08816, 2022 | | 2022 |
| Neural network training method, apparatus, electronic device, medium, and program product D Feng, L Lian, D Yu, X Yao, X Wu, Z Wu, Y Ma | | 2021 |
| Q-Diffusion: Quantizing Diffusion Models (Supplementary Materials) X Li, Y Liu, L Lian, H Yang, Z Dong, D Kang, S Zhang, K Keutzer | | |
| Bootstrapping Objectness from Videos by Relaxed Common Fate and Visual Grouping Supplementary Materials L Lian, Z Wu, SX Yu | | |
| Supplementary Materials: Unsupervised Visual Attention and Invariance for Reinforcement Learning X Wang, L Lian, XY Stella | | |
Stella X. YuProfessor of EECS, University of MichiganEmail verificata su umich.edu
