| Automatic Perturbation Analysis for Scalable Certified Robustness and Beyond K Xu*, Z Shi*, H Zhang*, Y Wang, KW Chang, M Huang, B Kailkhura, ... Advances in Neural Information Processing Systems, 2020 | 228 | 2020 |
| On the Adversarial Robustness of Vision Transformers R Shao, Z Shi, J Yi, PY Chen, CJ Hsieh TMLR, 2022 | 178 | 2022 |
| Robustness Verification for Transformers Z Shi, H Zhang, KW Chang, M Huang, CJ Hsieh International Conference on Learning Representations, 2020 | 119 | 2020 |
| A Deep Sequential Model for Discourse Parsing on Multi-Party Dialogues Z Shi, M Huang Proceedings of the AAAI Conference on Artificial Intelligence, 2019 | 82 | 2019 |
| Fast Certified Robust Training with Short Warmup Z Shi*, Y Wang*, H Zhang, J Yi, CJ Hsieh Advances in Neural Information Processing Systems, 2021 | 51 | 2021 |
| On the Sensitivity and Stability of Model Interpretations in NLP F Yin, Z Shi, CJ Hsieh, KW Chang Proceedings of the 60th Annual Meeting of the Association for Computational …, 2022 | 27* | 2022 |
| Red teaming language model detectors with language models Z Shi, Y Wang, F Yin, X Chen, KW Chang, CJ Hsieh Transactions of the Association for Computational Linguistics 12, 174-189, 2024 | 25 | 2024 |
| Efficiently Computing Local Lipschitz Constants of Neural Networks via Bound Propagation Z Shi, Y Wang, H Zhang, Z Kolter, CJ Hsieh Advances in Neural Information Processing Systems, 2022 | 21 | 2022 |
| Robustness to Modification with Shared Words in Paraphrase Identification Z Shi, M Huang Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020 | 19 | 2020 |
| Robust text captchas using adversarial examples R Shao, Z Shi, J Yi, PY Chen, CJ Hsieh 2022 IEEE International Conference on Big Data (Big Data), 1495-1504, 2022 | 15 | 2022 |
| Knowledge-Aided Open-Domain Question Answering M Zhou, Z Shi, M Huang, X Zhu arXiv preprint arXiv:2006.05244, 2020 | 14 | 2020 |
| On the Convergence of Certified Robust Training with Interval Bound Propagation Y Wang*, Z Shi*, Q Gu, CJ Hsieh International Conference on Learning Representations, 2022 | 9 | 2022 |
| Effective robustness against natural distribution shifts for models with different training data Z Shi, N Carlini, A Balashankar, L Schmidt, CJ Hsieh, A Beutel, Y Qin Advances in Neural Information Processing Systems 36, 2024 | 6 | 2024 |
| Towards robustness certification against universal perturbations Y Zeng*, Z Shi*, M Jin, F Kang, L Lyu, CJ Hsieh, R Jia The Eleventh International Conference on Learning Representations, 2023 | 5 | 2023 |
| Formal Verification for Neural Networks with General Nonlinearities via Branch-and-Bound Z Shi, Q Jin, H Zhang, Z Kolter, S Jana, CJ Hsieh | 4 | 2023 |
| Improving the Generation Quality of Watermarked Large Language Models via Word Importance Scoring Y Li, Y Wang, Z Shi, CJ Hsieh arXiv preprint arXiv:2311.09668, 2023 | 1 | 2023 |
| Lyapunov-stable Neural Control for State and Output Feedback: A Novel Formulation for Efficient Synthesis and Verification L Yang, H Dai, Z Shi, CJ Hsieh, R Tedrake, H Zhang arXiv preprint arXiv:2404.07956, 2024 | | 2024 |
| Defending LLMs against Jailbreaking Attacks via Backtranslation Y Wang, Z Shi, A Bai, CJ Hsieh arXiv preprint arXiv:2402.16459, 2024 | | 2024 |
| Learning Contextual Perturbation Budgets for Training Robust Neural Networks J Xu, Z Shi, H Zhang, J Yi, CJ Hsieh, L Wang | | 2020 |
Cho-Jui HsiehUniversity of California, Los AngelesVerified email at cs.ucla.edu
