A survey of large language models WX Zhao, K Zhou, J Li, T Tang, X Wang, Y Hou, Y Min, B Zhang, J Zhang, ... arXiv preprint arXiv:2303.18223, 2023 | 2438* | 2023 |
Large language models are zero-shot rankers for recommender systems Y Hou, J Zhang, Z Lin, H Lu, R Xie, J McAuley, WX Zhao European Conference on Information Retrieval, 364-381, 2024 | 192 | 2024 |
Recommendation as instruction following: A large language model empowered recommendation approach J Zhang, R Xie, Y Hou, WX Zhao, L Lin, JR Wen arXiv preprint arXiv:2305.07001, 2023 | 132 | 2023 |
AgentCF: Collaborative Learning with Autonomous Language Agents for Recommender Systems J Zhang, Y Hou, R Xie, W Sun, J McAuley, WX Zhao, L Lin, JR Wen | 24 | 2023 |
Prompting large language models for recommender systems: A comprehensive framework and empirical analysis L Xu, J Zhang, B Li, J Wang, M Cai, WX Zhao, JR Wen arXiv preprint arXiv:2401.04997, 2024 | 23 | 2024 |
Towards a more user-friendly and easy-to-use benchmark library for recommender systems L Xu, Z Tian, G Zhang, J Zhang, L Wang, B Zheng, Y Li, J Tang, Z Zhang, ... Proceedings of the 46th International ACM SIGIR Conference on Research and …, 2023 | 6 | 2023 |
Generative next-basket recommendation W Sun, R Xie, J Zhang, WX Zhao, L Lin, JR Wen Proceedings of the 17th ACM Conference on Recommender Systems, 737-743, 2023 | 3 | 2023 |
Distillation is All You Need for Practically Using Different Pre-trained Recommendation Models W Sun, R Xie, J Zhang, WX Zhao, L Lin, JR Wen arXiv preprint arXiv:2401.00797, 2024 | 2 | 2024 |
Sequence-level Semantic Representation Fusion for Recommender Systems L Xu, Z Tian, B Li, J Zhang, J Wang, M Cai, WX Zhao arXiv preprint arXiv:2402.18166, 2024 | | 2024 |