Yueqi Xie

Yueqi Xie 谢悦琪

I am a final-year Ph.D student in Department of Computer Science and Engineering at HKUST. I am also a visiting student researcher in Department of Sociology at Princeton University. My supervisors are Prof. Sunghun KIM and Prof. Qifeng Chen. I graduated from Peking University in 2020 with a bachelor's degree.

Email / Google Scholar

Research

I work on interdisciplinary study of AI and Social Science, including AI's social impact, socially responsible AI (AI safety, security, and privacy), and computational social science. My long-term goal is to understand and advance the relationship between AI and society, exploring both its technological and social dimensions.

Topics I currently focus on:

Socially Responsible Generative AI: [Nature Machine Intelligence'23], [ACL'24], [EMNLP'24], [KDD'25]

AI's Social Impact / Computational Social Science: Human-Contribution-Evaluation

Secure and Robust Federated Learning: [CVPR'23], [ICML'24], [CVPR'25]

Others:

Recommender Systems: [SIGIR'22], [WSDM'23], [RecSys'23a], [RecSys'23b], [WWW'24]

Image Compression: [ACMMM'21], [ICCV'21], [ECCV'22]

Education / Experience

2020-Now: Ph.D. Student in Computer Science, HKUST
2024/4-Now: Visiting Student Researcher in Sociology at Princeton University, Princeton
2023/3-2024/2: Visiting Student Researcher at Duke University, Remote
2022/3-2022/8: Research Intern at Microsoft Research Asia, Beijing
2016-2020: B.S. in Intelligence Science and Technology, Peking University
2019/6-2019/9: Visiting Student at HKUST, Hong Kong

Selected Work

(* joint first authors)

Full Publication List on Google Scholar.

Socially Responsible Generative AI

Defending ChatGPT against Jailbreak Attack via Self-Reminder
Yueqi Xie*, Jingwei Yi*, Jiawei Shao, Justin Curl, Lingjuan Lyu, Qifeng Chen, Xing Xie, Fangzhao Wu
Nature Machine Intelligence, 2023
/ / / Media Coverage: TechXplore, Tech Times

GradSafe: Detecting Jailbreak Prompts for LLMs via Safety-Critical Gradient Analysis
Yueqi Xie, Minghong Fang, Renjie Pi, Neil Gong
Annual Meeting of the Association for Computational Linguistics (ACL), 2024
/ /

Benchmarking and Defending Against Indirect Prompt Injection Attacks on Large Language Models
Jingwei Yi*, Yueqi Xie*, Bin Zhu, Emre Kiciman, Guangzhong Sun, Xing Xie, Fangzhao Wu
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2025
/ /

MLLM-Protector: Ensuring MLLM's Safety without Hurting Performance
Renjie Pi*, Tianyang Han*, Jianshu Zhang*, Yueqi Xie, Rui Pan, Qing Lian, Hanze Dong, Jipeng Zhang, Tong Zhang
The Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024
/ /

AI's Societal Impact / Computational Social Science

Measuring Human Contribution in AI-Assisted Content Generation
Yueqi Xie*, Tao Qi*, Jingwei Yi*, Ryan Whalen, Junming Huang, Qian Ding, Yu Xie, Xing Xie, Fangzhao Wu
Preprint, 2024
/ /

Secure and Robust Federated Learning

PoisonedFL: Model Poisoning Attacks to Federated Learning via Multi-Round Consistency
Yueqi Xie, Minghong Fang, Neil Gong
The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025
/

Defending against Model Poisoning Attacks for Federated Learning using Model Update Reconstruction Error
Yueqi Xie, Minghong Fang, Neil Gong
International Conference on Machine Learning (ICML), 2024
/ /

DYNAFED: Tackling Client Data Heterogeneity with Global Dynamics
Renjie Pi*, Weizhong Zhang*, Yueqi Xie*, Jiahui Gao, Xiaoyu Wang, Sunghun Kim, Qifeng Chen
The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023
/ /

Source code from Jon Barron, Aljaž Božič, XINTAO and Ekun.