Xuandong Zhao
E-mail: csxuandongzhao at gmail
Address: Goleta, CA 93106, USA
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Xuandong Zhao |
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E-mail: csxuandongzhao at gmail |
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| GitHub / LinkedIn / Twitter / Google Scholar |
I am a final-year CS Ph.D. student at UC Santa Barbara, advised by Prof. Yu-Xiang Wang and Prof. Lei Li. Previously, I graduated from the Department of Computer Science, Zhejiang University. During my undergrad, I was fortunate to work with Prof. Xi Li, Quanzheng Li, and Xiang Li. I also did internships in Alibaba DAMO Academy, Microsoft MSAI and Google Privacy Research. Currently, I am interested in Machine Learning and Natural Language Processing, with a particular focus on Responsible and Trustworthy Generative AI.
I am always open to collaborations. If you share similar interests or see potential synergies, please feel free to email me.
I am on the job market this year. I would be happy to discuss any opportunities that may be a good fit.
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Permute-and-Flip: An Optimally Robust and Watermarkable Decoder for LLMs Xuandong Zhao, Lei Li, Yu-Xiang Wang arXiv, 2024 [Paper] [Code] [Slides] |
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Weak-to-Strong Jailbreaking on Large Language Models Xuandong Zhao*, Xianjun Yang*, Tianyu Pang, Chao Du, Lei Li, Yu-Xiang Wang, William Yang Wang arXiv, 2024 [Paper] [Code] |
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Provable Robust Watermarking for AI-Generated Text Xuandong Zhao, Prabhanjan Ananth, Lei Li, Yu-Xiang Wang Proceedings of ICLR 2024 [Paper] [Code] [Video] [Demo] |
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Invisible Image Watermarks Are Provably Removable Using Generative AI Xuandong Zhao*, Kexun Zhang*, Zihao Su, Saastha Vasan, Ilya Grishchenko, Christopher Kruegel, Giovanni Vigna, Yu-Xiang Wang, Lei Li ICML 2023 Workshop on Challenges in Deploying Generative AI [Paper] [Code] [Video] [Media] |
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Protecting Language Generation Models via Invisible Watermarking Xuandong Zhao, Yu-Xiang Wang, Lei Li Proceedings of ICML 2023 [Paper] [Code] |
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Pre-trained Language Models Can be Fully Zero-Shot Learners Xuandong Zhao, Siqi Ouyang, Zhiguo Yu, Ming Wu, Lei Li Proceedings of ACL 2023, Oral [Paper] [Code] [Video] [Slides] |
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Distillation-Resistant Watermarking for Model Protection in NLP Xuandong Zhao, Lei Li, Yu-Xiang Wang Findings of EMNLP 2022 [Paper] [Code] [Video] [Blog] |
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Provably Confidential Language Modelling Xuandong Zhao, Lei Li, Yu-Xiang Wang Proceedings of NAACL 2022, Oral [Paper] [Code] [Video] |
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Compressing Sentence Representation for Semantic Retrieval via Homomorphic Projective Distillation Xuandong Zhao, Zhiguo Yu, Ming Wu, Lei Li Findings of ACL 2022 [Paper] [Code] [Video] [Poster] |
| Permute-and-Flip: An Optimally Robust and Watermarkable Decoder for LLMs Xuandong Zhao, Lei Li, Yu-Xiang Wang arXiv, 2024 [Paper] [Code] [Slides] |
| Weak-to-Strong Jailbreaking on Large Language Models Xuandong Zhao*, Xianjun Yang*, Tianyu Pang, Chao Du, Lei Li, Yu-Xiang Wang, William Yang Wang arXiv, 2024 [Paper] [Code] |
| Mapping the Increasing Use of LLMs in Scientific Papers Weixin Liang*, Yaohui Zhang*, Zhengxuan Wu*, Haley Lepp, Wenlong Ji, Xuandong Zhao, Hancheng Cao, Sheng Liu, Siyu He, Zhi Huang, Diyi Yang, Christopher Potts, Christopher D Manning, James Y. Zou arXiv, 2024 [Paper] |
| Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews Weixin Liang*, Zachary Izzo*, Yaohui Zhang*, Haley Lepp, Hancheng Cao, Xuandong Zhao, Lingjiao Chen, Haotian Ye, Sheng Liu, Zhi Huang, Daniel A. McFarland, James Y. Zou arXiv, 2024 [Paper] |
| DE-COP: Detecting Copyrighted Content in Language Models Training Data André Vicente Duarte, Xuandong Zhao, Arlindo L. Oliveira, Lei Li arXiv, 2024 [Paper] [Code] |
| GumbelSoft: Diversified Language Model Watermarking via the GumbelMax-trick Jiayi Fu, Xuandong Zhao, Ruihan Yang, Yuansen Zhang, Jiangjie Chen, Yanghua Xiao arXiv, 2024 [Paper] [Code] |
| Perils of Self-Feedback: Self-Bias Amplifies in Large Language Models Wenda Xu, Guanglei Zhu, Xuandong Zhao, Liangming Pan, Lei Li, William Yang Wang arXiv, 2024 [Paper] [Code] |
| Watermarking for Large Language Model Xuandong Zhao, Yu-Xiang Wang, Lei Li Tutorials of ACL 2024 |
| Provable Robust Watermarking for AI-Generated Text Xuandong Zhao, Prabhanjan Ananth, Lei Li, Yu-Xiang Wang Proceedings of ICLR 2024 [Paper] [Code] [Video] [Demo] |
| Invisible Image Watermarks Are Provably Removable Using Generative AI Xuandong Zhao*, Kexun Zhang*, Zihao Su, Saastha Vasan, Ilya Grishchenko, Christopher Kruegel, Giovanni Vigna, Yu-Xiang Wang, Lei Li ICML 2023 Workshop on Challenges in Deploying Generative AI [Paper] [Code] [Video] [Media] |
| A Survey on Detection of LLMs-Generated Content Xianjun Yang, Liangming Pan, Xuandong Zhao, Haifeng Chen, Linda Petzold, William Yang Wang, Wei Cheng arXiv, 2023 [Paper] [Code] |
| Private Prediction Strikes Back! Private Kernelized Nearest Neighbors with Individual Renyi Filter Yuqing Zhu, Xuandong Zhao, Chuan Guo, Yu-Xiang Wang Proceedings of UAI 2023, Spotlight [Paper] [Code] |
| Protecting Language Generation Models via Invisible Watermarking Xuandong Zhao, Yu-Xiang Wang, Lei Li Proceedings of ICML 2023 [Paper] [Code] |
| Pre-trained Language Models Can be Fully Zero-Shot Learners Xuandong Zhao, Siqi Ouyang, Zhiguo Yu, Ming Wu, Lei Li Proceedings of ACL 2023, Oral [Paper] [Code] [Video] [Slides] |
| Distillation-Resistant Watermarking for Model Protection in NLP Xuandong Zhao, Lei Li, Yu-Xiang Wang Findings of EMNLP 2022 [Paper] [Code] [Video] [Blog] |
| Provably Confidential Language Modelling Xuandong Zhao, Lei Li, Yu-Xiang Wang Proceedings of NAACL 2022, Oral [Paper] [Code] [Video] |
| Compressing Sentence Representation for Semantic Retrieval via Homomorphic Projective Distillation Xuandong Zhao, Zhiguo Yu, Ming Wu, Lei Li Findings of ACL 2022 [Paper] [Code] [Video] [Poster] |
| An Optimal Reduction of TV-Denoising to Adaptive Online Learning Dheeraj Baby, Xuandong Zhao, Yu-Xiang Wang Proceedings of AISTATS 2021 [Paper] [Code] |
| A Multi-Semantic Metapath Model for Large Scale Heterogeneous Network Representation Learning Xuandong Zhao, Jinbao Xue, Jin Yu, Xi Li, Hongxia Yang arXiv, 2020 [Paper] [Code] |
| Predicting Alzheimer's Disease by Hierarchical Graph Convolution from Positron Emission Tomography Imaging Jiaming Guo*, Wei Qiu*, Xiang Li*, Xuandong Zhao, Ning Guo, Quanzheng Li Proceedings of Big Data 2019 [Paper] [Code] |
| Multi-size Computer-aided Diagnosis of Positron Emission Tomography Images Using Graph Convolutional Networks Xuandong Zhao*, Xiang Li*, Ning Guo, Zhiling Zhou, Xiaxia Meng, Quanzheng Li Proceedings of ISBI 2019 [Paper] [Code] |
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UC Santa Barbara, USA Ph.D. student in Computer Science • Sept. 2019 - now |
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Zhejiang University, China B.E. in Computer Science • Sept. 2015 - June 2019, GPA: 3.96/4.00 |
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Chancellor's Fellowship, UC Santa Barbara, 2019, 2021, 2023 He Zhijun Scholarship (Highest honor in ZJU CS department), 2019 Alibaba-Zhejiang News Scholarship, 2018 National Scholarship (Top 0.2% Nationwide), 2016 First Prize in Chinese Physics Olympiad (CPhO; Top 0.1% in Shanxi Province, China), 2014 |
Last update: April 2024