Additional Campus Affiliations
Professor, Siebel School of Computing and Data Science
Professor, Statistics
Recent Publications
Ye, H., Huang, Z., Fang, C., Li, C. J., & Zhang, T. (Accepted/In press). Hessian-Aware Zeroth-Order Optimization. IEEE transactions on pattern analysis and machine intelligence. https://doi.org/10.1109/TPAMI.2025.3548810
Chen, S., Ma, S., So, A. M. C., & Zhang, T. (2024). Nonsmooth Optimization over the Stiefel Manifold and Beyond: Proximal Gradient Method and Recent Variants. SIAM Review, 66(2), 319-352. https://doi.org/10.1137/24M1628578
Diao, S., Wang, P., Lin, Y., Pan, R., Liu, X., & Zhang, T. (2024). Active Prompting with Chain-of-Thought for Large Language Models. In L.-W. Ku, A. F. T. Martins, & V. Srikumar (Eds.), Long Papers (pp. 1330-1350). (Proceedings of the Annual Meeting of the Association for Computational Linguistics; Vol. 1). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2024.acl-long.73
Diao, S., Pan, R., Dong, H., Shum, K. S., Zhang, J., Xiong, W., & Zhang, T. (2024). LMFlow: An Extensible Toolkit for Finetuning and Inference of Large Foundation Models. 116-127. Paper presented at 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL 2024, Hybrid, Mexico City, Mexico. https://doi.org/10.18653/v1/2024.naacl-demo.12
Dong, H., Xiong, W., Pang, B., Wang, H., Zhao, H., Zhou, Y., Jiang, N., Sahoo, D., Xiong, C., & Zhang, T. (2024). RLHF Workflow: From Reward Modeling to Online RLHF A Comprehensive Practical Alignment Recipe of Iterative Preference Learning. Transactions on Machine Learning Research, 2024.