Yueqi Xie 谢悦琪

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

My research focuses on building responsible and effective AI systems. I'm broadly interested in security, robustness, and effectiveness of Federated Learning, Recommender Systems, Computer Vision, and Large Language Models.

I was an intern in MSRA, working with Dr. Fangzhao Wu and Dr. Xing Xie. I'm fortunate to work with Dr. Minghong Fang and Dr. Neil Gong.

Email1  /  Email2  /  Google Scholar  /  Github

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News
  • Aug 2023: One paper is accepted to CIKM 2023.
  • June 2023: Two papers are accepted to RecSys 2023.
  • Feb 2023: One paper is accepted to CVPR 2023.
  • Oct 2022: One paper is accepted to WSDM 2023 (Best Paper Award Honorable Mention).
  • July 2022: One paper is accepted to ECCV 2022.
  • April 2022: One paper is accepted to SIGIR 2022.
  • July 2021: One paper is accepted to ICCV 2021.
  • July 2021: One paper is accepted to ACMMM 2021 (Oral).
Preprints
Robust Federated Learning against both Data Heterogeneity and Poisoning Attack via Aggregation Optimization
Yueqi Xie*, Weizhong Zhang*, Renjie Pi*, Fangzhao Wu, Qifeng Chen, Xing Xie, Sunghun Kim
Preprint, 2022
arXiv
Defending ChatGPT against Jailbreak Attack via Self-Reminder
Yueqi Xie*, Jingwei Yi*, Jiawei Shao, Justin Curl, Lingjuan Lyu, Qifeng Chen, Xing Xie, Fangzhao Wu
Preprint, 2023
Preprint
Publications (* joint first authors)
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
arXiv / Code
Attention Calibration for Transformer-based Sequential Recommendation
Peilin Zhou*, Qichen Ye*, Yueqi Xie, Jingqi Gao, Shoujin Wang, Jae Boum Kim, Chenyu You, Sunghun Kim
International Conference on Information and Knowledge Management (CIKM), 2023
arXiv
Equivariant Contrastive Learning for Sequential Recommendation
Peilin Zhou*, Jingqi Gao*, Yueqi Xie, Qichen Ye, Yining Hua, Sunghun Kim
ACM Conference on Recommender Systems (RecSys), 2023
arXiv
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
arXiv / Code
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
arXiv / Code
Decoupled Side Information Fusion for Sequential Recommendation
Yueqi Xie*, Peilin Zhou* and Sunghun Kim
International ACM SIGIR Conference (SIGIR), 2022
arXiv / Code
Optimizing Image Compression via Joint Learning with Denoising
Ka Leong Cheng*, Yueqi Xie* and Qifeng Chen
European Conference on Computer Vision (ECCV), 2022
arXiv / Code
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)
arXiv / Code
IICNet: A Generic Framework for Reversible Image Conversion
Ka Leong Cheng*, Yueqi Xie*, Qifeng Chen
International Conference on Computer Vision (ICCV), 2021
arXiv / Code
Awards
  • WSDM 2023 Best Paper Award Honorable Mention
  • Outstanding Graduate in Peking University, 2020
  • Peking University Scholarship, 2018-19

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