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.

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Research

I work on interdisciplinary study of AI and Social Science, including AI's societal 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 societal dimensions.

Topics I currently focus on:

Others:

Education / Experience

Selected Publications and Preprints

(* 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
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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
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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
Preprint, 2023
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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
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Secure and Robust Federated Learning
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
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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
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PoisonedFL: Model Poisoning Attacks to Federated Learning via Multi-Round Consistency
Yueqi Xie, Minghong Fang, Neil Gong
Preprint, 2024
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Recommender Systems
Rethinking Multi-Interest Learning for Candidate Matching in Recommender Systems
Yueqi Xie, Jingqi Gao, Peilin Zhou, Qichen Ye, Yining Hua, Jaeboum Kim, Fangzhao Wu, Sunghun Kim
ACM Conference on Recommender Systems (RecSys), 2023
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Efficiently Leveraging Multi-level User Intent for Session-based Recommendation via Atten-Mixer Network
Peiyan Zhang*, Jiayan Guo*, Chaozhuo Li*, Yueqi Xie, Jaeboum Kim, Yan Zhang, Xing Xie, Haohan Wang, Sunghun Kim
ACM International WSDM Conference (WSDM), 2023
Best Paper Award Honorable Mention (Top 4/690)
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Decoupled Side Information Fusion for Sequential Recommendation
Yueqi Xie*, Peilin Zhou* and Sunghun Kim
International ACM SIGIR Conference (SIGIR), 2022
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Image Compression
Optimizing Image Compression via Joint Learning with Denoising
Ka Leong Cheng*, Yueqi Xie* and Qifeng Chen
European Conference on Computer Vision (ECCV), 2022
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Enhanced Invertible Encoding for Learned Image Compression
Yueqi Xie*, Ka Leong Cheng* and Qifeng Chen
ACM International Conference on Multimedia (ACM MM), 2021
Full Oral Presentation (9% acceptance rate)
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IICNet: A Generic Framework for Reversible Image Conversion
Ka Leong Cheng*, Yueqi Xie*, Qifeng Chen
International Conference on Computer Vision (ICCV), 2021
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Source code from Jon Barron, Aljaž Božič, XINTAO and Ekun.