| Diffusion policies as an expressive policy class for offline reinforcement learning Z Wang, JJ Hunt, M Zhou arXiv preprint arXiv:2208.06193, 2022 | 601 | 2022 |
| Patch diffusion: Faster and more data-efficient training of diffusion models Z Wang, Y Jiang, H Zheng, P Wang, P He, Z Wang, W Chen, M Zhou Advances in neural information processing systems 36, 72137-72154, 2023 | 404 | 2023 |
| Diffusion-gan: Training gans with diffusion Z Wang, H Zheng, P He, W Chen, M Zhou arXiv preprint arXiv:2206.02262, 2022 | 397 | 2022 |
| Score identity distillation: Exponentially fast distillation of pretrained diffusion models for one-step generation M Zhou, H Zheng, Z Wang, M Yin, H Huang Forty-first International Conference on Machine Learning, 2024 | 141 | 2024 |
| In-context learning unlocked for diffusion models Z Wang, Y Jiang, Y Lu, P He, W Chen, Z Wang, M Zhou Advances in Neural Information Processing Systems 36, 8542-8562, 2023 | 98 | 2023 |
| Probabilistic conformal prediction using conditional random samples Z Wang, R Gao, M Yin, M Zhou, DM Blei arXiv preprint arXiv:2206.06584, 2022 | 41 | 2022 |
| One-step diffusion policy: Fast visuomotor policies via diffusion distillation Z Wang, Z Li, A Mandlekar, Z Xu, J Fan, Y Narang, L Fan, Y Zhu, Y Balaji, ... arXiv preprint arXiv:2410.21257, 2024 | 33 | 2024 |
| Adversarial score identity distillation: Rapidly surpassing the teacher in one step M Zhou, H Zheng, Y Gu, Z Wang, H Huang arXiv preprint arXiv:2410.14919, 2024 | 31 | 2024 |
| Guided Score identity Distillation for Data-Free One-Step Text-to-Image Generation M Zhou, Z Wang, H Zheng, H Huang arXiv preprint arXiv:2406.01561, 2024 | 30* | 2024 |
| Thompson sampling via local uncertainty Z Wang, M Zhou International Conference on Machine Learning, 10115-10125, 2020 | 29 | 2020 |
| Relative preference optimization: Enhancing llm alignment through contrasting responses across identical and diverse prompts Y Yin, Z Wang, Y Gu, H Huang, W Chen, M Zhou arXiv preprint arXiv:2402.10958, 2024 | 27 | 2024 |
| Implicit Distributional Reinforcement Learning Y Yue, Z Wang, M Zhou Advances in Neural Information Processing Systems 33, 7135-7147, 2020 | 26 | 2020 |
| Diffusion policies creating a trust region for offline reinforcement learning T Chen, Z Wang, M Zhou Advances in Neural Information Processing Systems 37, 50098-50125, 2024 | 25 | 2024 |
| Diffusion-rpo: Aligning diffusion models through relative preference optimization Y Gu, Z Wang, Y Yin, Y Xie, M Zhou arXiv preprint arXiv:2406.06382, 2024 | 24 | 2024 |
| A Behavior Regularized Implicit Policy for Offline Reinforcement Learning S Yang, Z Wang, H Zheng, Y Feng, M Zhou arXiv preprint arXiv:2202.09673, 2022 | 24 | 2022 |
| Beta diffusion M Zhou, T Chen, Z Wang, H Zheng Advances in Neural Information Processing Systems 36, 30070-30095, 2023 | 18 | 2023 |
| Stitch: Simultaneous thinking and talking with chunked reasoning for spoken language models CH Chiang, X Wang, L Li, CC Lin, K Lin, S Liu, Z Wang, Z Yang, H Lee, ... arXiv preprint arXiv:2507.15375, 2025 | 8 | 2025 |
| Audio-Aware Large Language Models as Judges for Speaking Styles CH Chiang, X Wang, CC Lin, K Lin, L Li, R Kopetz, Y Qian, Z Wang, ... arXiv preprint arXiv:2506.05984, 2025 | 8 | 2025 |
| Improving Data Efficiency for LLM Reinforcement Fine-tuning Through Difficulty-targeted Online Data Selection and Rollout Replay Y Sun, J Shen, Y Wang, T Chen, Z Wang, M Zhou, H Zhang arXiv preprint arXiv:2506.05316, 2025 | 7 | 2025 |
| Denoising score distillation: From noisy diffusion pretraining to one-step high-quality generation T Chen, Y Zhang, Z Wang, YN Wu, O Leong, M Zhou arXiv preprint arXiv:2503.07578, 2025 | 6 | 2025 |
Mingyuan ZhouProfessor, University of Texas at Austin; Microsoft AI SuperintelligenceVerified email at mccombs.utexas.edu
