Additional Campus Affiliations
Professor, Siebel School of Computing and Data Science
Professor, Statistics
Recent Publications
Chen, Y., Peng, H., Zhang, T., & Ji, H. (2026). Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training. Transactions on Machine Learning Research, 2026-March.
Hao, Y., & Zhang, T. (2026). The Surprising Harmfulness of Benign Overfitting for Adversarial Robustness. IEEE Transactions on Information Theory, 72(8), 6023-6053. https://doi.org/10.1109/TIT.2026.3702992
Huang, J., Madala, S., Sidhu, R., Niu, C., Peng, H., Hockenmaier, J., & Zhang, T. (2026). Tackling Distractor Documents in Multi-Hop QA with Reinforcement and Curriculum Learning. In 19th Conference of the European Chapter of the Association for Computational Linguistics, Findings of EACL 2026 (pp. 5548-5561). (19th Conference of the European Chapter of the Association for Computational Linguistics, Findings of EACL 2026). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2026.findings-eacl.294
Wang, Z., Chen, X., Li, G., Ji, H., & Zhang, T. (2026). When Test-Time Training Fails: A Critical Analysis of Robustness and Hyperparameter Sensitivity. Transactions on Machine Learning Research, 2026-June.
Ye, H., Xiong, W., & Zhang, T. (2026). PMGT-VR: A Decentralized Proximal-Gradient Algorithmic Framework With Variance Reduction. IEEE transactions on pattern analysis and machine intelligence, 48(1), 408-420. https://doi.org/10.1109/TPAMI.2025.3606874