Chejian Xu

I am a second year Computer Science Ph.D. student at University of Illinois, Urbana-Champaign (UIUC), advised by Prof. Bo Li. I received my Bachelor's degree from Computer Science, Zhejiang University at CKC Honors College, advised by Prof. Shouling Ji and Prof. Siliang Tang.

My current research interests are focused on advancing the security, robustness, and generalization of machine learning (ML) systems. My work delves into the intriguing intersection of these critical aspects, particularly within the domains of natural language processing (NLP) and reinforcement learning (RL). My primary goal is to develop innovative methodologies and techniques that enhance the reliability and trustworthiness of ML models, such as language models (LMs), within these domains.

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2023/12 - Our paper, DecodingTrust, received the Outstanding Paper award at NeurIPS 2023.
2023/09 - One paper got accepted to NeurIPS 2023.
2023/03 - We are hosting the Secure and Safe Autonomous Driving (SSAD) Workshop and Challenge at CVPR 2023!
2022/10 - Received the NeurIPS 2022 Scholar Award.
2022/09 - One paper got accepted to NeurIPS 2022.
2022/05 - One paper got accepted to Findings of NAACL 2022.
2022/04 - One paper got accepted to IJCAI 2022.


DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Boxin Wang, Weixin Chen, Hengzhi Pei, Chulin Xie, Mintong Kang, Chenhui Zhang, Chejian Xu, Zidi Xiong, Ritik Dutta, Rylan Schaeffer, Sang T. Truong, Simran Arora, Mantas Mazeika, Dan Hendrycks, Zinan Lin, Yu Cheng, Sanmi Koyejo, Dawn Song, Bo Li
Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), 2023
(Outstanding Paper)
[PDF] [Code] [Website]

DiffScene: Diffusion-Based Safety-Critical Scenario Generation for Autonomous Vehicles

Chejian Xu, Ding Zhao, Alberto Sangiovanni-Vincentelli, Bo Li
Workshop on New Frontiers in Adversarial Machine Learning at ICML 2023

SafeBench: A Benchmarking Platform for Safety Evaluation of Autonomous Vehicles

Chejian Xu*, Wenhao Ding*, Weijie Lyu, Zuxin Liu, Shuai Wang, Yihan He, Hanjiang Hu, Ding Zhao, Bo Li
Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS), 2022
[PDF] [Code] [Leaderboard] [BibTeX]

A Survey on Safety-Critical Driving Scenario Generation -- A Methodological Perspective

Wenhao Ding, Chejian Xu, Mansur Arief, Haohong Lin, Bo Li, Ding Zhao
IEEE Transactions on Intelligent Transportation Systems (T-ITS), March, 2023
[PDF] [BibTeX]

SemAttack: Natural Textual Attacks via Different Semantic Spaces

Boxin Wang*, Chejian Xu*, Xiangyu Liu, Yu Cheng, Bo Li
North American Chapter of the Association for Computational Linguistics (NAACL), 2022 (Findings)
[PDF] [Code] [BibTeX]

Copy Motion From One to Another: Fake Motion Video Generation

Zhenguang Liu, Sifan Wu, Chejian Xu, Xiang Wang, Lei Zhu, Shuang Wu, Fuli Feng
31st International Joint Conference on Artificial Intelligence (IJCAI), 2022
[PDF] [Code] [BibTeX]

COPA: Certifying Robust Policies for Offline Reinforcement Learning against Poisoning Attacks

Fan Wu*, Linyi Li*, Chejian Xu, Huan Zhang, Bhavya Kailkhura, Krishnaram Kenthapadi, Ding Zhao, Bo Li
The Tenth International Conference on Learning Representations (ICLR), 2022
[PDF] [Code] [Leaderboard] [BibTeX]

Adversarial GLUE: A Multi-Task Benchmark for Robustness Evaluation of Language Models

Boxin Wang*, Chejian Xu*, Shuohang Wang, Zhe Gan, Yu Cheng, Jianfeng Gao, Ahmed Hassan Awadallah, Bo Li
Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS), 2021 (Oral)
[PDF] [Leaderboard] [Dataset] [BibTeX]


Conference Reviewer: NeurIPS 2022-2023, AAAI 2023-2024, AACL 2022
Journal Reviewer: IEEE T-ITS
Organizer: CVPR 2023 SSAD Workshop and Challenge, NeurIPS 2022 DMLW Workshop
Program Committee: ICLR 2023 RTML Workshop

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