I am a PhD student at Berkeley Artificial Intelligence Research Lab (BAIR), advised by Prof. Kurt Keutzer. Previously, I completed my undergrad in Tsinghua University. During this time, I was fortunate to be advised by Prof. Jianfei Chen and Prof. Jun Zhu in TSAIL, and Prof. Tuo Zhao in Georgia Tech.

Research Interests

My research interests spans a couple of topics in efficient machine learning, particularly efficient training and inference. A list of my interests and some related projects:

• Diffusion Language Model
• Speculative Decoding
• Large Reasoning Model
• Dynamic Sparse Training

Selected Publications

• Residual Context Diffusion Language Models [arXiv] [Code] [Project page] [Models]

  Yuezhou Hu*, Harman Singh*, Monishwaran Maheswaran*, Haocheng Xi, Coleman Hooper, Jintao Zhang, Aditya Tomar, Michael W. Mahoney, Sewon Min, Mehrdad Farajtabar, Kurt Keutzer, Amir Gholami, Chenfeng Xu

  Preprint

• Arbitrage: Efficient Reasoning via Advantage-Aware Speculation [arXiv] [Project page]

  Monishwaran Maheswaran*, Rishabh Tiwari*, Yuezhou Hu*, Kerem Dilmen, Coleman Hooper, Haocheng Xi, Nicholas Lee, Mehrdad Farajtabar, Michael Mahoney, Kurt Keutzer, Amir Gholami

  Preprint

• AdaSPEC: Selective Knowledge Distillation for Efficient Speculative Decoders [arXiv] [OpenReview] [Project page]

  Yuezhou Hu*, Jiaxin Guo*, Xinyu Feng, Tuo Zhao

  Neural Information Processing Systems (NeurIPS), 2025 (Spotlight)

• S-STE: Continuous Pruning Function for Efficient 2:4 Sparse Pre-training [arXiv] [OpenReview] [Project page]

  Yuezhou Hu, Jun Zhu, Jianfei Chen

  Neural Information Processing Systems (NeurIPS), 2024

• Accelerating Transformer Pre-training with 2:4 Sparsity [arXiv] [OpenReview] [PDF] [Project page]

  Yuezhou Hu, Kang Zhao, Weiyu Huang, Jianfei Chen, Jun Zhu

  International Conference on Machine Learning (ICML), 2024

Contact

Feel free to contact me via email or ask me any questions at my Askbox.