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 currently a Postdoctoral Researcher at UC Berkeley as part of the RDI and BAIR, working with Prof. Dawn Song. I earned my PhD in Computer Science from UC Santa Barbara, where I was advised by Prof. Yu-Xiang Wang and Prof. Lei Li. Prior to that, I graduated with a Bachelor's degree in Computer Science from Zhejiang University. I have also interned at leading tech companies including Alibaba, Microsoft and Google.
My current research interests lie in Machine Learning, Natural Language Processing, and AI Safety, with a particular focus on Responsible Generative AI. I am always open to collaborations. If you share similar interests or see potential synergies, please feel free to reach out via email!
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An Undetectable Watermark for Generative Image Models Sam Gunn*, Xuandong Zhao*, Dawn Song NeurIPS 2024 Safe Generative AI Workshop [Paper] [Code] |
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Permute-and-Flip: An Optimally Robust and Watermarkable Decoder for LLMs Xuandong Zhao, Lei Li, Yu-Xiang Wang NeurIPS 2024 Safe Generative AI Workshop [Paper] [Code] [Slides] |
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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 Proceedings of NeurIPS 2024 [Paper] [Code] [Video] [Media] |
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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 ICML 2024 the Next Generation of AI Safety Workshop [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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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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Provably Confidential Language Modelling Xuandong Zhao, Lei Li, Yu-Xiang Wang Proceedings of NAACL 2022, Oral [Paper] [Code] [Video] |
| An Undetectable Watermark for Generative Image Models Sam Gunn*, Xuandong Zhao*, Dawn Song NeurIPS 2024 Safe Generative AI Workshop [Paper] [Code] |
| Permute-and-Flip: An Optimally Robust and Watermarkable Decoder for LLMs Xuandong Zhao, Lei Li, Yu-Xiang Wang NeurIPS 2024 Safe Generative AI Workshop [Paper] [Code] [Slides] |
| Efficiently Identifying Watermarked Segments in Mixed-Source Texts Xuandong Zhao*, Chenwen Liao*, Yu-Xiang Wang, Lei Li NeurIPS 2024 Safe Generative AI Workshop [Paper] |
| An Examination of AI-Generated Text Detectors Across Multiple Domains and Models Brian Tufts, Xuandong Zhao, Lei Li NeurIPS 2024 Safe Generative AI Workshop [Paper] |
| Multimodal Situational Safety Kaiwen Zhou*, Chengzhi Liu*, Xuandong Zhao, Anderson Compalas, Dawn Song, Xin Eric Wang NeurIPS 2024 RBFM Workshop, Oral [Paper] [Code] [Website] [Dataset] |
| Evaluating Durability: Benchmark Insights into Multimodal Watermarking Jielin Qiu*, William Han*, Xuandong Zhao, Shangbang Long, Christos Faloutsos, Lei Li arXiv, 2024 [Paper] [Code] [Website] |
| ClinicalLab: Aligning Agents for Multi-Departmental Clinical Diagnostics in the Real World Weixiang Yan, Haitian Liu, Tengxiao Wu, Qian Chen, Wen Wang, Haoyuan Chai, Jiayi Wang, Weishan Zhao, Yixin Zhang, Renjun Zhang, Li Zhu, Xuandong Zhao arXiv, 2024 [Paper][Code] |
| CodeHalu: Investigating Code Hallucinations in LLMs via Execution-based Verification Yuchen Tian*, Weixiang Yan*, Qian Yang, Xuandong Zhao, Qian Chen, Wen Wang, Ziyang Luo, Lei Ma, Dawn Song arXiv, 2024 [Paper][Code] |
| Watermarking for Large Language Model Xuandong Zhao, Yu-Xiang Wang, Lei Li Tutorials of NeurIPS 2024, Tutorials of ACL 2024 [Paper] [Website] [Video] |
| Bileve: Securing Text Provenance in Large Language Models Against Spoofing with Bi-level Signature Tong Zhou, Xuandong Zhao, Xiaolin Xu, Shaolei Ren Proceedings of NeurIPS 2024 [Paper] |
| 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 Proceedings of NeurIPS 2024 [Paper] [Code] [Video] [Media] |
| Erasing the Invisible: A Stress-Test Challenge for Image Watermarks Mucong Ding*, Tahseen Rabbani*, Bang An*, Souradip Chakraborty, Chenghao Deng, Mehrdad Saberi, Yuxin Wen, Xuandong Zhao, Mo Zhou, Anirudh Satheesh, Mary-Anne Hartley, Lei Li, Yu-Xiang Wang, Vishal M. Patel, Soheil Feizi, Tom Goldstein, Furong Huang Competitions of NeurIPS 2024 [Paper] [Website] |
| MarkLLM: An Open-Source Toolkit for LLM Watermarking Leyi Pan, Aiwei Liu, Zhiwei He, Zitian Gao, Xuandong Zhao, Yijian Lu, Binglin Zhou, Shuliang Liu, Xuming Hu, Lijie Wen, Irwin King, Philip S. Yu System Demonstrations of EMNLP, 2024 [Paper] [Code] [Colab] |
| A Survey on Detection of LLMs-Generated Content Xianjun Yang, Liangming Pan, Xuandong Zhao, Haifeng Chen, Linda Petzold, William Yang Wang, Wei Cheng Findings of EMNLP 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 Proceedings of COLM 2024 [Paper] [Code] |
| Weak-to-Strong Jailbreaking on Large Language Models Xuandong Zhao*, Xianjun Yang*, Tianyu Pang, Chao Du, Lei Li, Yu-Xiang Wang, William Yang Wang ICML 2024 the Next Generation of AI Safety Workshop [Paper] [Code] |
| 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 Proceedings of ICML 2024, Oral [Paper] [Code] |
| DE-COP: Detecting Copyrighted Content in Language Models Training Data André Vicente Duarte, Xuandong Zhao, Arlindo L. Oliveira, Lei Li Proceedings of ICML 2024 [Paper] [Code] |
| GumbelSoft: Diversified Language Model Watermarking via the GumbelMax-trick Jiayi Fu, Xuandong Zhao, Ruihan Yang, Yuansen Zhang, Jiangjie Chen, Yanghua Xiao Proceedings of ACL 2024 [Paper] [Code] |
| Pride and Prejudice: LLM Amplifies Self-Bias in Self-Refinement Wenda Xu, Guanglei Zhu, Xuandong Zhao, Liangming Pan, Lei Li, William Yang Wang Proceedings of ACL 2024, Oral [Paper] [Code] |
| Provable Robust Watermarking for AI-Generated Text Xuandong Zhao, Prabhanjan Ananth, Lei Li, Yu-Xiang Wang Proceedings of ICLR 2024 [Paper] [Code] [Video] [Demo] |
| 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. in Computer Science • Sept. 2019 - June 2024 |
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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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AdvML Rising Star Award, 2024 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: Oct. 2024