| Enhanced Invertible Encoding for Learned Image Compression Y Xie, KL Cheng, Q Chen ACM International Conference on Multimedia (ACM MM), 2021 | 112 | 2021 |
| Decoupled Side Information Fusion for Sequential Recommendation Y Xie, P Zhou, S Kim International ACM SIGIR Conference (SIGIR), 2022 | 63 | 2022 |
| Efficiently Leveraging Multi-level User Intent for Session-based Recommendation via Atten-Mixer Network P Zhang, J Guo, C Li, Y Xie, J Kim, Y Zhang, X Xie, H Wang, S Kim Web Search and Data Mining (WSDM), Best Paper Award Honorable Mention, 2023 | 45 | 2023 |
| Defending chatgpt against jailbreak attack via self-reminders Y Xie, J Yi, J Shao, J Curl, L Lyu, Q Chen, X Xie, F Wu Nature Machine Intelligence 5 (12), 1486-1496, 2023 | 39* | 2023 |
| IICNet: A Generic Framework for Reversible Image Conversion KL Cheng, Y Xie, Q Chen International Conference on Computer Vision (ICCV), 2021 | 21 | 2021 |
| Llmrec: Benchmarking large language models on recommendation task J Liu, C Liu, P Zhou, Q Ye, D Chong, K Zhou, Y Xie, Y Cao, S Wang, ... arXiv preprint arXiv:2308.12241, 2023 | 16 | 2023 |
| Equivariant Contrastive Learning for Sequential Recommendation P Zhou, J Gao, Y Xie, Q Ye, Y Hua, S Kim ACM Conference on Recommender Systems (RecSys), 2023 | 15 | 2023 |
| Optimizing Image Compression via Joint Learning with Denoising KL Cheng, Y Xie, Q Chen European Conference on Computer Vision (ECCV), 2022 | 15 | 2022 |
| Benchmarking and defending against indirect prompt injection attacks on large language models J Yi, Y Xie, B Zhu, E Kiciman, G Sun, X Xie, F Wu arXiv preprint arXiv:2312.14197, 2023 | 14 | 2023 |
| Exploring recommendation capabilities of gpt-4v (ision): A preliminary case study P Zhou, M Cao, YL Huang, Q Ye, P Zhang, J Liu, Y Xie, Y Hua, J Kim arXiv preprint arXiv:2311.04199, 2023 | 14 | 2023 |
| Rethinking Multi-Interest Learning for Candidate Matching in Recommender Systems Y Xie, J Gao, P Zhou, Q Ye, Y Hua, J Kim, F Wu, S Kim ACM Conference on Recommender Systems (RecSys), 2023 | 13 | 2023 |
| MLLM-Protector: Ensuring MLLM's Safety without Hurting Performance R Pi, T Han, Y Xie, R Pan, Q Lian, H Dong, J Zhang, T Zhang arXiv preprint arXiv:2401.02906, 2024 | 10 | 2024 |
| DYNAFED: Tackling Client Data Heterogeneity with Global Dynamics R Pi, W Zhang, Y Xie, J Gao, X Wang, S Kim, Q Chen Computer Vision and Pattern Recognition (CVPR), 2023 | 8 | 2023 |
| Robust federated learning against both data heterogeneity and poisoning attack via aggregation optimization Y Xie, W Zhang, R Pi, F Wu, Q Chen, X Xie, S Kim arXiv preprint arXiv:2211.05554, 2022 | 5* | 2022 |
| Is Contrastive Learning Necessary? A Study of Data Augmentation vs Contrastive Learning in Sequential Recommendation P Zhou, YL Huang, Y Xie, J Gao, S Wang, JB Kim, S Kim The Web Conference (WWW), 2024 | | 2024 |
| GradSafe: Detecting Unsafe Prompts for LLMs via Safety-Critical Gradient Analysis Y Xie, M Fang, R Pi, N Gong arXiv preprint arXiv:2402.13494, 2024 | | 2024 |
Qifeng ChenHKUSTVerified email at ust.hk
