Chaowei Xiao
Email: cxiao34@wisc.edu
I am Chaowei Xiao, an assistant professor at the University of Wisconsin, Madison, and a research scientist at NVIDIA .
I am currently very interested in exploring the safety and security of Large Language Model Systems and studying the role of LLMs in different application domains.
I obtained my Ph.D. from the University of Michigan, Ann Arbor, and my bachelor's degree from Tsinghua University. Before joining UW-Madison, I spent two years at NVIDIA as a full-time research scientist and a wonderful year at ASU.
Award
- [2024] USENIX Security Distinguished Paper Award.
- [2024] Schmidt Sciences AI2050 Early Career Fellow
- [2024] ACM Gordon Bell Final list
- [2024] My PhD student Xiaogeng Won NVIDIA Fellowship on Security track
- [2024] Selected in Stanford/Elsevier Top 2% Scientists List 2024
- [2023] ACM Gordon Bell Special Prize for HPC-Based COVID-19 Research
- [2023] Impact Award from Argonne National Laboratory.
- [2021] International Confrence on Embedded Wireless Systems and Networks(EWSN) Best Paper Award
- [2014] MobiCom Best Paper Award
Recent Invited talks
- [12/2024] Invited talk at SFU@NeurIPS
- [12/2024] Invited talk at LLM and Agent Safety Competition@NeurIPS.
- [10/2024] Keynote at CCS Workshop on Large AI Systems and Models with Privacy and Safety Analysis.
- [10/2024] Invited talk at Trillion Parameter Consortium (TPC) on LLM safety and security
- [10/2024] Invited talk at NSF Workshop on Large Language Models for Network Security
- [06/2024] Invited talk at CVPR Workshop of Adversarial Machine Learning on Computer Vision: Robustness of Foundation Models
- [06/2024] Talk at NAACL tutorial on Combating Security and Privacy Issues in the Era of Large Language Models
- [05/2024] Invited talk at ICLR Secure and Trustworthy Large Language Models
- [12/2023] Invited Talk at NeurIPS TDW workshop
Recent News
- [1/2025] We have 9 papers at ICLR and 3 papers at NAACL on Model Safety and Security. Congratulations to all authors.
- [12/2024] I will give an invited talk at SFU@NeurIPS and LLM and Agent Safety Competition at NeurIPS.
- [12/2024] We got the Fall Research Competition Award at UW-Madison. Thank you UW-Madison and OVCR.
- [11/2024] Our group recently received funding and donations. Thank you Amazon and Apple.
- [11/2024] Our lab will have a winter break this Dec. Lab members will enjoy some well-deserved vacation time, with their families and loved ones.
- [09/2024] We have four papers at NeurIPS regular track.
- [09/2024]Our study on safety of RLFH Alignment is accepted to S&P (Oakland) 2025
- [07/2024] MultiModal jailbreak benchmark is accepted to COLM. It is from the interns in my group.
- [07/2024] 4/4 papers are accepted to ECCV on the topic of trustworthy VLM and driving. Two of them are from interns in my group.
- [06/2024] Senior Area Chair for NeurIPS Benchmark track
- [06/2024] I am currently serving as AC for the NeurIPS regular track
- [05/2024] Our jailbreak paper is accepted to USENIX Security. Congratulations, Zhiyuan!
- [03/2024] Five papers at NAACL on LLM security (4 main and 1 finding): two on the backdoor attack, one on backdoor defense, one on jailbreak attacks, and one on model fingerprint. Stay tuned on these exciting fields
- [03/2024] PreDa for personalized federated learning is accepted at CVPR 2024.
- [01/2024] Three papers at ICLR.
- [01/2024] Two papers at TMLR
- [12/2023] Invited Talk at NeurIPS TDW workshop
- [10/2023]Our paper MoleculeSTM has been accepted to Nature Machine Intelligence. MoleculeSTM aims to align the nature language and molecule representation into the same representation space.
- [10/2023] Three papers at EMNLP and one paper at NeurIPS. For our NeurIPS paper, we study a new threat of the instruction tuning of LLMs by injecting the Ads. This is the first work that views the LLMs as the generative model and aims to attack the generative property of LLMs.
- [10/2023] Our tutorial on Security and Privacy in the Era of Large Language Models is accepted to NAACL.
- [05/2023] One paper at ACL. Congratulations to zhuofeng and jiazhao. We propose an attention-based method to defend against NLP backdoor attacks
- [04/2023] Two papers at ICML. Congratulations to Jiachen and Zhiyuan. We propose the first benchmark for code copyright of code generation models.
- [02/2023] Two papers at CVPR. Congratulations to Yiming and Xiaogeng. Xiaogeng is an intern from my group at ASU.
- [02/2023] I will give a tutorial at CVPR 2023 on the topic of trustworthiness in the era of Foundation Models. Stay tuned!
- [01/2023] Impact Award from Argonne National Laboratory.
- [01/2023] One paper got accepted to USENIX Security 2023.
- [1/2023] Three papers are accepted to ICLR 2023 [a]: We explain why and how to use diffusion model to improve adversarial robustness and design DensePure which leverages the pretrained diffusion model and classifier to provide the state-of-the-art certified robustness. [b]:This is our first attemp on retrieval-based framework and AI for drug discovery. We will recently release more work in this research line. Stay tuned!
- [12/2022] Our team won the ACM Gordon Bell Special Prize for COVID-19 Research.
- [09/2022] One papers got accepted to USENIX Security 2023.
- [09/2022] Two papers got accepted to NeurIPS 2022.
- [09/2022] Our paper RobustTraj has been accepted to CORL for oral presentations. We explore to train a robust Trajectory Prediction Model against adversarial attacks.
- [08/2022] I will be giving a talk in virtual seminar series on Challenges and Opportunities for Security & Privacy in Machine Learning.
- [07/2022] One survey paper to discuss the challenge and opportunity of machine learning security got accepted to ACM Computing Survey 2022.
- [07/2022] Two papers got accepted to ECCV 2022.
- [05/2022] Two papers got accepted to ICML 2022. Thanks for all of my collaborators.
- [3/2022] I will be giving a talk in AAAI 2022 1st International Workshop on Practical Deep Learning in the Wild.
- [3/2022] I will be giving a talk in AAAI 2022 workshop on Adversarial Machine Learning and Beyond.
- [2/2022] One paper is accepted to ICLR.
More
Preprints
- [New][Agent Security] A New Era in LLM Security: Exploring Security Concerns in Real-World LLM-based Systems.
Fangzhou Wu, Ning Zhang, Somesh Jha, Patrick McDaniel, Chaowei Xiao.
https://arxiv.org/abs/2402.18649
Selected Publications ([Full List])
(* represents equal contribution)
- [LLM Security] AutoDAN-Turbo: A Lifelong Agent for Strategy Self-Exploration to Jailbreak LLMs
Xiaogeng Liu*, Peiran Li*, G. Edward Suh, Yevgeniy Vorobeychik, Zhuoqing Mao, Somesh Jha, Patrick McDaniel, Huan Sun, Bo Li, Chaowei Xiao
ICLR 2024 - [LLM Security]Can Watermarks be Used to Detect LLM IP Infringement For Free?
Zhengyue Zhao, Xiaogeng Liu, Somesh Jha, Patrick McDaniel, Bo Li, Chaowei Xiao
ICLR 2024 - [Agent Security] EIA: Environmental Injection Attack on Generalist Web Agent for Privacy Leakage.
Zeyi Liao, Lingbo Mo, Chejian Xu, Mintong Kang, Jiawei Zhang, Chaowei Xiao, Yuan Tian, Bo Li, Huan Sun
- [LLM for Science]LeanAgent: Lifelong Learning for Formal Theorem Proving.
Adarsh Kumarappan, Mo Tiwari, Peiyang Song, Robert Joseph George, Chaowei Xiao, Anima Anandkumar.
ICLR 2024 - [LLM Safety (Hallucination)]HaloScope: Harnessing Unlabeled LLM Generations for Hallucination Detection.
Xuefeng Du, Chaowei Xiao, Yixuan Li
NeurIPS 2024 (Oral) - [LLM Security] Mitigating Fine-tuning Jailbreak Attack with Backdoor Enhanced Alignment.
Jiongxiao Wang, Jiazhao Li, Yiquan Li, Xiangyu Qi, Muhao Chen, Junjie Hu, Yixuan Li, Bo Li, Chaowei Xiao
NeurIPS 2024 - [LLM For Driving] Dolphins: Multimodal Language Model for Driving.
Yingzi Ma, Yulong Cao, Jiachen Sun, Marco Pavone, Chaowei Xiao
ECCV 2024 - [ Embodied Agent] Voyager: An Open-Ended Embodied Agent with Large Language Models.
Guanzhi Wang, Yuqi Xie, Yunfan Jiang, Ajay Mandlekar, Chaowei Xiao, Yuke Zhu, Linxi Fan, Anima Anandkumar
TMLR 2024 - [LLM Fingerprint]Instructional fingerprinting of large language models.
Jiashu Xu, Fei Wang, Mingyu Derek Ma, Pang Wei Koh, Chaowei Xiao, Muhao Chen.
NAACL 2024. - [LLM Security]AutoDAN: Generating Stealthy Jailbreak Prompts on Aligned Large Language Models.
Xiaogeng Liu, Nan Xu, Muhao Chen, Chaowei Xiao.
ICLR 2024. - [LLM Security]On the exploitability of instruction tuning.
Manli Shu, Jiongxiao Wang, Chen Zhu, Jonas Geiping, Chaowei Xiao*, Tom Goldstein*.
- [LLM Copyright]CodeIPPrompt: Intellectual Property Infringement Assessment of Code Language Models
Zhiyuan Yu, Yuhao Wu, Ning Zhang, Chenguang Wang, Yevgeniy Vorobeychik, Chaowei Xiao
- [Diffusion & Security] Diffusion Models for Adversarial Purification
Weili Nie, Brandon Guo, Yujia Huang,Chaowei Xiao, Arash Vahdat, Anima Anandkumar.
- [Diffusion & Security] DensePure: Understanding Diffusion Models towards Adversarial Robustness.
Chaowei Xiao*, Zhongzhu Chen*, Kun Jin*, Jiongxiao Wang*, Weili Nie, Mingyan Liu, Anima Anandkumar, Bo Li, Dawn Song
- [ViT & Robustness] Understanding the robustness in vision transformers.
Daquan Zhou, Zhiding Yu, Enze Xie,Chaowei Xiao, Anima Anandkumar, Jiashi Feng, Jose M Alvarez.
- [Robustness] AugMax: Adversarial Composition of RandomAugmentations for Robust Training.
Haotao Wang,Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Animashree Anandkumar, Zhangyang Wang.
NeurIPS 2021
- [Security] Invisible for both Camera and LiDAR: Security of Multi-Sensor Fusion based Perception in Autonomous Driving Under Physical-World Attacks.
Yulong Cao*, Ningfei Wang*,Chaowei Xiao*, Dawei Yang*, Jin Fang, RuigangYang, Qi Alfred Chen, Mingyan Liu, Bo Li.
IEEE Symposium on Security and Privacy (Oakland) 2021
- [Security] Spatially Transformed Adversarial Examples
Chaowei Xiao*, Jun-Yan Zhu*, Bo Li, Warren He, Mingyan Liu and Dawn Song
In International Conference on Learning Representations (ICLR), 2018 [pdf]
- [Security] Generating Adversarial Examples with Adversarial Networks
Chaowei Xiao, Bo Li, Jun-Yan Zhu, Warren He, Mingyan Liu and Dawn Song
In International Joint Conference on Artificial Intelligence (IJCAI), 2018. [pdf]
- [Security] Robust Physical-World Attacks on Machine Learning Models
Kevin Eykholt*, Ivan Evtimov*, Earlence Fernandes, Bo Li, Amir Rahmati, Chaowei Xiao, Atul Prakash, Tadayoshi Kohno and Dawn Song
In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018 [pdf]
Full Publications
(* represents equal contribution)
2025
- Preference Poisoning Attacks on Reward Model Learning
Junlin Wu, Jiongxiao Wang, Chaowei Xiao, Chenguang Wang, Ning Zhang, Yevgeniy Vorobeychik.
- AutoDAN-Turbo: A Lifelong Agent for Strategy Self-Exploration to Jailbreak LLMs
Xiaogeng Liu*, Peiran Li*, G. Edward Suh, Yevgeniy Vorobeychik, Zhuoqing Mao, Somesh Jha, Patrick McDaniel, Huan Sun, Bo Li, Chaowei Xiao.
- Can Watermarks be Used to Detect LLM IP Infringement For Free?
Zhengyue Zhao, Xiaogeng Liu, Somesh Jha, Patrick McDaniel, Bo Li, Chaowei Xiao.
- Benchmarking Vision Language Model Unlearning via Fictitious Facial Identity Dataset
Yingzi Ma*, Jiongxiao Wang*, Fei Wang, Siyuan Ma, Jiazhao Li, Jinsheng Pan, Xiujun Li, Furong Huang, Lichao Sun, Bo Li, Yejin Choi, Muhao Chen, Chaowei Xiao.
- CVE-Bench: Benchmarking LLM-based Software Engineering Agent’s Ability to Repair Real-World CVE Vulnerabilities
Peiran Wang, Xiaogeng Liu, Chaowei Xiao.
- RePD: Defending Jailbreak Attack through a Retrieval-based Prompt Decomposition Process
Peiran Wang, Xiaogeng Liu, Chaowei Xiao.
- Test-time Backdoor Mitigation for Black-Box Large Language Models with Defensive Demonstrations
Wenjie Jacky Mo, Jiashu Xu, Qin Liu, Jiongxiao Wang, Jun Yan, Hadi Askari, Chaowei Xiao, Muhao Chen.
- T-Stitch: Accelerating Sampling in Pre-Trained Diffusion Models with Trajectory Stitching
Zizheng Pan, Bohan Zhuang, De-An Huang, Weili Nie, Zhiding Yu, Chaowei Xiao, Jianfei Cai, Anima Anandkumar.
- LeanAgent: Lifelong Learning for Formal Theorem Proving.
Adarsh Kumarappan, Mo Tiwari, Peiyang Song, Robert Joseph George, Chaowei Xiao, Anima Anandkumar.
- MuirBench: A Comprehensive Benchmark for Robust Multi-image Understanding
Fei Wang, Xingyu Fu, James Y. Huang, Zekun Li, Qin Liu, Xiaogeng Liu, Mingyu Derek Ma, Nan Xu, Wenxuan Zhou, Kai Zhang, Tianyi Lorena Yan, Wenjie Jacky Mo, Hsiang-Hui Liu, Pan Lu, Chunyuan Li, Chaowei Xiao, Kai-Wei Chang, Dan Roth, Sheng Zhang, Hoifung Poon, Muhao Chen.
- DataGen: Unified Synthetic Dataset Generation via Large Language Models
Yue Huang, Siyuan Wu, Chujie Gao, Dongping Chen, Qihui Zhang, Yao Wan, Tianyi Zhou, Chaowei Xiao, Jianfeng Gao, Xiangliang Zhang, Lichao Sun.
- EIA: Environmental Injection Attack on Generalist Web Agents for Privacy Leakage
Zeyi Liao, Lingbo Mo, Chejian Xu, Mintong Kang, Jiawei Zhang, Chaowei Xiao, Yuan Tian, Bo Li, Huan Sun.
- Robust Representation Consistency Model via Contrastive Denoising
Jiachen Lei, Julius Berner, Jiongxiao Wang, Zhongzhu Chen, Chaowei Xiao, Zhongjie Ba, Kui Ren, Jun Zhu, Anima Anandkumar.
2024
- BackAlign: Mitigating Fine-tuning based Jailbreak Attack with Backdoor Enhanced Safety Alignment
Jiongxiao Wang, Jiazhao Li, Yiquan Li, Xiangyu Qi, Junjie Hu, Yixuan Li, Patrick McDaniel, Muhao Chen, Bo Li, Chaowei Xiao
- HaloScope: Harnessing Unlabeled LLM Generations for Hallucination Detection
Xuefeng Du, Chaowei Xiao, Yixuan Li.
- Consistency Purification: Effective and Efficient Diffusion Purification towards Certified Robustness
Yiquan Li, Zhongzhu Chen, Kunjin, Jiongxiao Wang, Bo Li, Chaowei Xiao.
- AgentPoison: Red-teaming LLM Agents via Memory or Knowledge Base Backdoor Poisoning
Zhaorun Chen, Zhen Xiang, Chaowei Xiao, Dawn Song, Bo Li. .
- Jailbreakv-28k: A benchmark for assessing the robustness of multimodal large language models against jailbreak attacks
Weidi Luo*, Siyuan Ma*, Xiaogeng Liu, Xiaoyu Guo, Chaowei Xiao.
- Dolphins: Multi-
modal Language Model for Driving.
Yingzi Ma, Yulong Cao, Jiachen Sun, Marco Pavone, Chaowei Xiao.
- AdaShield: Safeguarding Multimodal Large Language Models from Structure-based Attack via Adaptive Shield Prompting.
Yu Wang, Xiaogeng Liu, Yu Li, Muhao Chen, Chaowei Xiao.
- RealGen: Retrieval Augmented Generation for Controllable Tra c Scenarios.
Wenhao Ding, Yulong Cao, Ding Zhao, Chaowei Xiao, Marco Pavone.
- Leveraging Hierarchical Feature Sharing for E cient Dataset Condensation.
Haizhong Zheng, Jiachen Sun, Shutong Wu,Bhavya Kaikhura, Zhuoqing Mao, Chaowei Xiao, Atul Prakash.
- On the exploitability of reinforcement learning with human feedback for large language models.
Jiongxiao Wang, Junlin Wu, Muhao Chen, Yevgeniy Vorobeychik, Chaowei Xiao.
- Position Paper: TrustLLM: Trustworthiness in Large Language Models.
TrustLLM Team.
- PerAda: Parameter-E cient Federated Learning Personalization with Generalization Guarantees.
Chulin Xie, De-An Huang, Wenda Chu, Daguang Xu, Chaowei Xiao*, Bo Li*, and Anima Anandkumar*.
- Do Not Listen To Me: Understanding and Exploring Jailbreak Prompts of Large Language Models.
Zhiyuan Yu, Xiaogeng Liu, Shuning Liang, Zach Cameron,Chaowei Xiao, Ning Zhang.
- Reinforcement Learning with Human Feedback for Realistic Tra c Simulation.
Yulong Cao, Boris Ivanovic, Chaowei Xiao, Marco Pavone.
- AutoDan: Generating stealthy jailbreak prompts on aligned large language models.
Xiaogeng Liu, Nan Xu, Muhao Chen, Chaowei Xiao
- ChatGPT-powered Conversational Drug Editing Using Retrieval and Domain Feedback
Shengchao Liu, Jiongxiao Wang, Yijin Yang, Chengpeng Wang, Ling Liu, Hongyu Guo, Chaowei Xiao
- CALICO: Self-Supervised Camera-LiDAR Contrastive Pre-training for BEV Perception.
Jiachen Sun, Haizhong Zheng, Qingzhao Zhang, Atul Prakash, Z. Morley Mao, and Chaowei Xiao
- ChatGPT as an Attack Tool: Stealthy Textual Backdoor Attack via Blackbox Generative Model Trigger.
Jiazhao Li, Yijin Yang, Zhuofeng Wu, V.G.Vinod Vydiswaran, Chaowei Xiao.
- Instructional Fingerprinting of Large Language Models.
Jiashu Xu, Fei Wang, Mingyu Derek Ma, Pang Wei Koh, Chaowei Xiao, Muhao Chen.
- Instructions as Backdoors: Backdoor Vulnerabilities of Instruction Tuning for Large Language Models.
Jiashu Xu, Fei Wang, Mingyu Derek Ma, Pang Wei Koh, Chaowei Xiao, Muhao Chen.
- From Shortcuts to Triggers: Backdoor Defense with Denoised PoE.
Qin Liu, Fei Wang, Chaowei Xiao, Muhao Chen.
- Cognitive Overload: Jailbreaking Large Language Models with Overloaded Logical Thinking.
Nan Xu, Fei Wang, Ben Zhou, Bangzheng Li, Chaowei Xiao, Muhao Chen.
- Prismer: A Vision-Language Model with Multi-Task Experts
Shikun Liu, Linxi Fan, Edward Johns, Zhiding Yu, Chaowei Xiao, Anima Anandkumar.
- Voyager: An open-ended embodied agent with large language models
Guanzhi Wang, Yuqi Xie, Yunfan Jiang, Ajay Mandlekar, Chaowei Xiao, Yuke Zhu, Linxi Fan, Anima Anandkumar
- Multi-modal molecule structure–text model for text-based retrieval and editing
Shengchao Liu, Weili Nie, Chengpeng Wang, Jiarui Lu, Zhuoran Qiao, Ling Liu, Jian Tang*, Chaowei Xiao*, Animashree Anandkumar*.
- Differentially Private Video Activity Recognition.
Zelun Luo, Yuliang Zou, Yijin Yang, Zane Durante, De-An Huang, Zhiding Yu, , Chaowei Xiao, Li Fei-Fei, Animashree Anandkumar.
- Semantic Adversarial Attacks via Diffusion Models.
Chenan Wang, Jinhao Duan, Chaowei Xiao, Edward Kim, Matthew Stamm, Kaidi Xu.
2023
- Shall We Pretrain Autoregressive Language Models with Retrieval? A Comprehensive Study
Boxin Wang, Wei Ping, Peng Xu, Lawrence McAfee, Zihan Liu, Mohammad Shoeybi, Yi Dong, Oleksii Kuchaiev, Bo Li, Chaowei Xiao, Anima Anandkumar, Bryan Catanzaro
- Re-ViLM: Retrieval-Augmented Visual Language Model for Zero and Few-Shot Image Captioning
Zhuolin Yang, Wei Ping, Zihan Liu, Vijay Anand Korthikanti, Weili Nie, De-An Huang, Linxi Fan, Zhiding Yu, Shiyi Lan, Bo Li, Mohammad Shoeybi, Ming-Yu Liu, Yuke Zhu, Bryan Catanzaro, Chaowei Xiao*, Anima Anandkumar*
- HiCL: Hierarchical Contrastive Learning of Unsupervised Sentence Embeddings
Zhuofeng Wu, Chaowei Xiao, V.G.Vinod Vydiswaran
- On the Exploitability of Instruction Tuning
Manli Shu, Jiongxiao Wang, Chen Zhu, Jonas Geiping, Chaowei Xiao*, Tom Goldstein*
- [LLM Safety]Defending against Insertion-based Textual Backdoor Attacks via Attribution.
Jiazhao Li, Zhuofeng Wu, Wei Ping, Chaowei Xiao, V.G. Vinod Vydiswaran.
ACL 2023
- CodeIPPrompt: Intellectual Property Infringement Assessment of Code Language Models
Zhiyuan Yu, Yuhao Wu, Ning Zhang, Chenguang Wang, Yevgeniy Vorobeychik, Chaowei Xiao
- A Critical Revisit of Adversarial Robustness in 3D Point Cloud Recognition with Diffusion-Driven Purification.
Jiachen Sun, Jiongxiao Wang, Weili Nie, Zhiding Yu, Zhuoqing Mao, Chaowei Xiao
- VoxFormer: Sparse Voxel Transformer for Camera-based 3D Semantic Scene Completion.
Yiming Li, Zhiding Yu, Chris Choy, Chaowei Xiao, Jose M. Alvarez, Sanja Fidler, Chen Feng, Anima Anandkumar
- Expunging Clean-label Invisible Poisons via Pre-trained Diffusion Models.
Xiaogeng Liu, Minghui Li, Haoyu Wang, Shengshan Hu, Dengpan Ye, Hai Jin, Libing Wu,Chaowei Xiao.
- DiffSmooth: Certifiably Robust Learning via Diffusion Models and Local Smoothing.
Jiawei Zhang, , Zhongzhu Chen, Huan Zhang, Chaowei Xiao, Bo Li.
- DensePure: Understanding Diffusion Models towards Adversarial Robustness.
Chaowei Xiao*, Zhongzhu Chen*, Kun Jin*, Jiongxiao Wang*, Weili Nie, Mingyan Liu, Anima Anandkumar, Bo Li, Dawn Song
- Defending against Adversarial Audio via Diffusion Model
Shutong Wu, Jiongxiao Wang, Wei Ping, Weili Nie,Chaowei Xiao
- Retrieval-based Controllable Molecule Generation
Zichao Wang, Weili Nie, Zhuoran Qiao, Chaowei Xiao , Richard Baraniuk, Anima Anandkumar
- Semantically Meaningful Adversarial Audio Attack
Zhiyuan Yu, Yuanhaur Chang, Ning Zhang, Chaowei Xiao
- GenSLMs: Genome-scale language
models reveal SARS-CoV-2 evolutionary dynamics.
Maxim Zvyagin*, Alexander Brace*, Kyle Hippe*, Yuntian Deng*, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael Irvin, J. Gregory Pauloski, Logan Ward, Valerie Hayot, Murali Emani, Sam Foreman, Zhen Xie, Diangen Lin, Maulik Shukla, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Ian Foster, James J. Davis, Michael E. Papka, Thomas Brettin, Rick Stevens, Anima Anandkumar, Venkatram Vishwanath, Arvind Ramanathan.
2022
- Test-Time Prompt Tuning for Zero-Shot Generalization in Vision-Language Models
Manli Shu, Weili Nie, De-An Huang, Zhiding Yu, Tom Goldstein, Anima Anandkumar, Chaowei Xiao
- Exploring the Limits of Domain-Adaptive Training for Detoxifying Large-Scale Language Models
Boxin Wang, Wei Ping, Chaowei Xiao, Peng Xu, Mostofa Patwary, Mohammad Shoeybi, Bo Li, Anima Anandkumar, Bryan Catanzaro.
- Robust Trajectory Prediction against Adversarial Attacks
Yulong Cao, Danfei Xu, Xinshuo Weng, Z. Morley Mao, Anima Anandkuma, Chaowei Xiao, Marco Pavone
- Diffusion Models for Adversarial Purification
Weili Nie, Brandon Guo, Yujia Huang,Chaowei Xiao, Arash Vahdat, Anima Anandkumar.
- Understanding the robustness in vision transformers.
Daquan Zhou, Zhiding Yu, Enze Xie,Chaowei Xiao, Anima Anandkumar, Jiashi Feng, Jose M Alvarez.
- AdvDO: Realistic Adversarial Attacks for
Trajectory Prediction
Yulong Cao,Chaowei Xiao, Anima Anandkumar, Danfei Xu, Marco Pavone.
- SecretGen: Privacy Recovery on Pre-trained Models
Zhuowen Yuan, Fan Wu, Yunhui Long,Chaowei Xiao, Bo Li
- Taxonomy of Machine Learning Safety: A Survey and Primer
Sina Mohseni, Zhiding Yu, Chaowei Xiao Jay Yadawa, Haotao Wang and Zhangyang Wang
ACM Computing Survey 2022[pdf]
- RelViT: Concept-guided Vision Transformer for Visual Relational Reasoning
Xiaojian Ma, Weili Nie, Zhiding Yu, Huaizu Jiang,Chaowei Xiao, Yuke Zhu, Song-Chun Zhu, Anima Anandkumar
- Characterizing Attacks on Deep Reinforcement Learning.
Xinlei Pan*,Chaowei Xiao*, Warren He, Shuang Yang, Peng Jian, Mingjie Sun, Mingyan Liu, Bo Li, Dawn Song.
AAMAS 2022 [pdf]
2021
- Adversarially Robust 3D Point Cloud Recognition Using Self-Supervisions.
Jiachen Sun, Yulong Cao, Christopher Choy, Zhiding Yu, Anima Anandkumar, Z. Morley Mao, Chaowei Xiao.
NeurIPS 2021
- AugMax: Adversarial Composition of RandomAugmentations for Robust Training.
Haotao Wang,Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Animashree Anandkumar, Zhangyang Wang.
NeurIPS 2021
- Efficient Transformers for Language and Vision.
Chen Zhu, Wei Ping,Chaowei Xiao, Mohammad Shoeybi, Tom Goldstein, Anima Anandkumar, Bryan Catanzaro.
NeurIPS 2021 (84.1% Top-1 accuracy solely trained on ImageNet-1K)
- Can Shape Structure Features Improve Model Robustness?
Mingjie Sun*, Zichao Li*,Chaowei Xiao*, Haonan Qiu, Bhavya Kailkhura, MingyanLiu, Bo Li.
ICCV 2021
- Invisible for both Camera and LiDAR: Security of Multi-Sensor Fusion based Perception in Autonomous Driving Under Physical-World Attacks.
Yulong Cao*, Ningfei Wang*,Chaowei Xiao*, Dawei Yang*, Jin Fang, RuigangYang, Qi Alfred Chen, Mingyan Liu, Bo Li.
IEEE Symposium on Security and Privacy (Oakland) 2021
- Application-Driven Privacy-Preserving Data Publishing with Correlated Attributes.
Aria Rezaei,Chaowei Xiao, Jie Gao, Bo Li, Sirajum Munir.
Embedded Wireless Systems and Networks (EWSN 2021)Best Paper Award
- Behavior Privacy Perserving in RF Sensing.
Jianwie Liu,Chaowei Xiao, Kaiyan Cui, Jinsong Han, Xian Xu, Kui Ren.
IEEE Transcations on Dependable and Secure Computing. [pdf]
2020
- SemanticAdv: Generating Adversarial Examples via Attribute-conditional Image Editing
Haonan Qiu*, Chaowei Xiao*, Lei Yang*, Xinchen Yan, Honglak Lee, Bo Li.
ECCV 2020
- Robust Deep Reinforcement Learning against Adversarial Perturbations on State Observations
Huan Zhang*, Hongge Chen*, Chaowei Xiao, Bo Li, Mingyan Liu, Duane Boning, Cho-Jui Hsieh.
NeurIPS 2020 (Spotlight).
- Towards Stable and Efficient Training of Verifiably Robust Neural Networks
Huan Zhang, Hongge Chen, Chaowei Xiao, Sven Gowal, Robert Stanforth, Bo Li, Duane Boning, Cho-Jui Hsieh.
ICLR 2020.
2019
- AdvIT: Adversarial Frames Identifier Based on Temporal Consistency In Videos
Chaowei Xiao, Ruizhi Deng, Bo Li, Taesung Lee, Jinfeng Yi, Ian Molloy, Mingyan Liu, Dawn Song
In International Conference on Computer Vision (ICCV) 2019.
- MeshAdv: Adversarial Meshes for Visual Recognition
Chaowei Xiao*, Dawei Yang*, Bo Li, Jia Deng, Mingyan Liu
In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2019. (Oral presentation) [pdf]
- Performing Co-Membership Attack Against Deep Generative Model
Kin Sum Liu, Chaowie Xiao , Bo Li, Jie Gao
In IEEE International Conference on Data Mining (ICDM) 2019
- Improving Robustness of ML Classifiers against Realizable Evasion Attacks Using Conserved Features
Liang Tong, Bo Li, Chen Hajaj, Chaowei Xiao, Ning Zhang, Yevgeniy Vorobeychik.
In USENIX Security 2019.
- Adversarial Sensor Attack on LIDAR-based Perception in Autonomous Driving
Yulong Cao, Chaowei Xiao, Benjamin Cyr, Yimeng Zhou, Won Park, Sara Rampazzi, Qi Alfred Chen, Kevin Fu, Z. Morely Map
In the 26th ACM Conference on Computer and Communications Security (CCS'19) [pdf]
2018
- Characterizing Adversarial Examples Based on Spatial Consistency Information for Semantic Segmentation
Chaowei Xiao, Duizhi Deng, Bo Li, Fisher Yu, Mingyan Liu and Dawn Song
In European Conference on Computer Vision (ECCV), 2018 [pdf][supplementary material]
- Spatially Transformed Adversarial Examples
Chaowei Xiao*, Jun-Yan Zhu*, Bo Li, Warren He, Mingyan Liu and Dawn Song
In International Conference on Learning Representations (ICLR), 2018 [pdf]
- Generating Adversarial Examples with Adversarial Networks
Chaowei Xiao, Bo Li, Jun-Yan Zhu, Warren He, Mingyan Liu and Dawn Song
In International Joint Conference on Artificial Intelligence (IJCAI), 2018. [pdf]
- From Behavior Similarity to Symptom Similarity: Using Community Detection for Early Discovery of Software Exploits
Chaowei Xiao, Armin Sarabi,Yang Liu , Bo Li, Mingyan Liu and Tudor Dumitras
In USENIX Security Symposium (USENIX Security), 2018 [pdf]
- Robust Physical-World Attacks on Machine Learning Models
Kevin Eykholt*, Ivan Evtimov*, Earlence Fernandes, Bo Li, Amir Rahmati, Chaowei Xiao, Atul Prakash, Tadayoshi Kohno and Dawn Song
In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018 [pdf]
Before 2018
- Static Power of Mobile Devices: Self-updating Radio Maps for Wireless Indoor Localization
Chenshu Wu, Zheng Yang, Chaowei Xiao, Chaofan Yang, Yunhao Liu and Mingyan Liu
In IEEE International Conference on Computer Communications (INFOCOM), 2015
- Tagoram: Real-time Tracking of Mobile RFID Tags to High Precision Using COTS Devices.
Lei Yang, Yekui Chen, Xiangyang Li, Chaowei Xiao, Mo Li and Yunhao Liu
In International Conference on Mobile Computing and Networking (MobiCom), 2014. Best Paper Award
