| The emergence of reproducibility and consistency in diffusion models H Zhang, J Zhou, Y Lu, M Guo, P Wang, L Shen, Q Qu Forty-first International Conference on Machine Learning, 2023 | 40 | 2023 |
| Dissecting distribution inference A Suri, Y Lu, Y Chen, D Evans 2023 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML), 150-164, 2023 | 12 | 2023 |
| Improving Training Efficiency of Diffusion Models via Multi-Stage Framework and Tailored Multi-Decoder Architecture H Zhang, Y Lu, I Alkhouri, S Ravishankar, D Song, Q Qu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 11* | 2024 |
| Exploring low-dimensional subspaces in diffusion models for controllable image editing S Chen, H Zhang, M Guo, Y Lu, P Wang, Q Qu arXiv preprint arXiv:2409.02374, 2024 | 6 | 2024 |
| ELFS: Enhancing Label-Free Coreset Selection via Clustering-based Pseudo-Labeling H Zheng, E Tsai, Y Lu, J Sun, BR Bartoldson, B Kailkhura, A Prakash arXiv preprint arXiv:2406.04273, 2024 | 1 | 2024 |
| TreeBoN: Enhancing Inference-Time Alignment with Speculative Tree-Search and Best-of-N Sampling J Qiu, Y Lu, Y Zeng, J Guo, J Geng, H Wang, K Huang, Y Wu, M Wang arXiv preprint arXiv:2410.16033, 2024 | | 2024 |
