Predict Future Sales using Ensembled Random Forests. - Yuwei Zhang; Xin Wu; Chenyang Gu; Yueqi Xie (CoRR, 2019)

IICNet: A Generic Framework for Reversible Image Conversion. - Ka Leong Cheng; Yueqi Xie; Qifeng Chen (ICCV, 2021)

Enhanced Invertible Encoding for Learned Image Compression. - Yueqi Xie; Ka Leong Cheng; Qifeng Chen (ACM Multimedia, 2021)

Optimizing Image Compression via Joint Learning with Denoising. - Ka Leong Cheng; Yueqi Xie; Qifeng Chen (ECCV (19), 2022)

Decoupled Side Information Fusion for Sequential Recommendation. - Yueqi Xie; Peilin Zhou; Sunghun Kim 001 (SIGIR, 2022)

Equivariant Contrastive Learning for Sequential Recommendation. - Peilin Zhou; Jingqi Gao; Yueqi Xie; Qichen Ye; Yining Hua; Sunghun Kim 001 (CoRR, 2022)

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 001; Sunghun Kim 001 (CoRR, 2022)

Attention Calibration for Transformer-based Sequential Recommendation. - Peilin Zhou; Qichen Ye; Yueqi Xie; Jingqi Gao; Shoujin Wang; Jae Boum Kim; Chenyu You; Sunghun Kim 001 (CIKM, 2023)

DYNAFED: Tackling Client Data Heterogeneity with Global Dynamics. - Renjie Pi; Weizhong Zhang; Yueqi Xie; Jiahui Gao; Xiaoyu Wang; Sunghun Kim 001; Qifeng Chen (CVPR, 2023)

Rethinking Multi-Interest Learning for Candidate Matching in Recommender Systems. - Yueqi Xie; Jingqi Gao; Peilin Zhou; Qichen Ye; Yining Hua; Jae Boum Kim; Fangzhao Wu; Sunghun Kim 001 (RecSys, 2023)

Equivariant Contrastive Learning for Sequential Recommendation. - Peilin Zhou; Jingqi Gao; Yueqi Xie; Qichen Ye; Yining Hua; Jaeboum Kim; Shoujin Wang; Sunghun Kim 001 (RecSys, 2023)

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 001; Haohan Wang; Sunghun Kim 001 (WSDM, 2023)

LLMRec: Benchmarking Large Language Models on Recommendation Task. - Junling Liu; Chao Liu 001; Peilin Zhou; Qichen Ye; Dading Chong; Kang Zhou; Yueqi Xie; Yuwei Cao; Shoujin Wang; Chenyu You; Philip S. Yu (CoRR, 2023)

Exploring Recommendation Capabilities of GPT-4V(ision): A Preliminary Case Study. - Peilin Zhou; Meng Cao 002; You-Liang Huang; Qichen Ye; Peiyan Zhang; Junling Liu; Yueqi Xie; Yining Hua; Jaeboum Kim (CoRR, 2023)

Benchmarking and Defending Against Indirect Prompt Injection Attacks on Large Language Models. - Jingwei Yi; Yueqi Xie; Bin Zhu 008; Keegan Hines; Emre Kiciman; Guangzhong Sun; Xing Xie 001; Fangzhao Wu (CoRR, 2023)

Defending ChatGPT against jailbreak attack via self-reminders. - Yueqi Xie; Jingwei Yi; Jiawei Shao; Justin Curl; Lingjuan Lyu; Qifeng Chen; Xing Xie 001; Fangzhao Wu (Nat. Mac. Intell., 2023)

GradSafe: Detecting Jailbreak Prompts for LLMs via Safety-Critical Gradient Analysis. - Yueqi Xie; Minghong Fang; Renjie Pi; Neil Gong 001 (ACL (1), 2024)

MLLM-Protector: Ensuring MLLM's Safety without Hurting Performance. - Renjie Pi; Tianyang Han; Jianshu Zhang 003; Yueqi Xie; Rui Pan 002; Qing Lian; Hanze Dong; Jipeng Zhang; Tong Zhang 001 (EMNLP, 2024)

FedREDefense: Defending against Model Poisoning Attacks for Federated Learning using Model Update Reconstruction Error. - Yueqi Xie; Minghong Fang; Neil Zhenqiang Gong (ICML, 2024)

Is Contrastive Learning Necessary? A Study of Data Augmentation vs Contrastive Learning in Sequential Recommendation. - Peilin Zhou; You-Liang Huang; Yueqi Xie; Jingqi Gao; Shoujin Wang; Jae Boum Kim; Sunghun Kim 001 (WWW, 2024)

MLLM-Protector: Ensuring MLLM's Safety without Hurting Performance. - Renjie Pi; Tianyang Han; Yueqi Xie; Rui Pan 002; Qing Lian; Hanze Dong; Jipeng Zhang; Tong Zhang 001 (CoRR, 2024)

GradSafe: Detecting Unsafe Prompts for LLMs via Safety-Critical Gradient Analysis. - Yueqi Xie; Minghong Fang; Renjie Pi; Neil Zhenqiang Gong (CoRR, 2024)

PoisonedFL: Model Poisoning Attacks to Federated Learning via Multi-Round Consistency. - Yueqi Xie; Minghong Fang; Neil Zhenqiang Gong (CoRR, 2024)

Measuring Human Contribution in AI-Assisted Content Generation. - Yueqi Xie; Tao Qi; Jingwei Yi; Ryan Whalen; Junming Huang 001; Qian Ding; Yu Xie; Xing Xie 001; Fangzhao Wu (CoRR, 2024)

Model Poisoning Attacks to Federated Learning via Multi-Round Consistency. - Yueqi Xie; Minghong Fang; Neil Zhenqiang Gong (CVPR, 2025)

Benchmarking and Defending against Indirect Prompt Injection Attacks on Large Language Models. - Jingwei Yi; Yueqi Xie; Bin Zhu 008; Emre Kiciman; Guangzhong Sun; Xing Xie 001; Fangzhao Wu (KDD (1), 2025)

When Large Vision Language Models Meet Multimodal Sequential Recommendation: An Empirical Study. - Peilin Zhou; Chao Liu 001; Jing Ren 010; Xinfeng Zhou; Yueqi Xie; Meng Cao 002; Zhongtao Rao; You-Liang Huang; Dading Chong; Junling Liu; Jae Boum Kim; Shoujin Wang; et al. (WWW, 2025)

Variance reduction in output from generative AI. - Yu Xie; Yueqi Xie (CoRR, 2025)

Uncovering inequalities in new knowledge learning by large language models across different languages. - Chenglong Wang 004; Haoyu Tang; Xiyuan Yang; Yueqi Xie; Jina Suh; Sunayana Sitaram; Junming Huang 001; Yu Xie; Zhaoya Gong; Xing Xie 001; Fangzhao Wu (CoRR, 2025)

Evidencing Unauthorized Training Data from AI Generated Content using Information Isotopes. - Tao Qi; Jinhua Yin; Dongqi Cai 001; Yueqi Xie; Huili Wang; Hu Zhiyang; Peiru Yang; Guoshun Nan; Zhili Zhou 001; Shangguang Wang; Lingjuan Lyu; Yongfeng Huang 001; et al. (CoRR, 2025)

Defending against Indirect Prompt Injection by Instruction Detection. - Tongyu Wen; Chenglong Wang 004; Xiyuan Yang; Haoyu Tang; Yueqi Xie; Lingjuan Lyu; Zhicheng Dou; Fangzhao Wu (CoRR, 2025)