| Towards open-world recommendation with knowledge augmentation from large language models Y Xi, W Liu, J Lin, J Zhu, B Chen, R Tang, W Zhang, R Zhang, Y Yu arXiv preprint arXiv:2306.10933, 2023 | 63 | 2023 |
| How can recommender systems benefit from large language models: A survey J Lin, X Dai, Y Xi, W Liu, B Chen, H Zhang, Y Liu, C Wu, X Li, C Zhu, ... arXiv preprint arXiv:2306.05817, 2023 | 26 | 2023 |
| A Bird's-eye View of Reranking: from List Level to Page Level Y Xi, J Lin, W Liu, X Dai, W Zhang, R Zhang, R Tang, Y Yu In Proceedings of the Sixteenth ACM International Conference on Web Search …, 2022 | 17 | 2022 |
| Multi-Level Interaction Reranking with User Behavior History Y Xi, W Liu, J Zhu, X Zhao, X Dai, R Tang, W Zhang, R Zhang, Y Yu Proceedings of the 45th International ACM SIGIR Conference on Research and …, 2022 | 13 | 2022 |
| Neural Re-ranking in Multi-stage Recommender Systems: A Review W Liu, Y Xi, J Qin, F Sun, B Chen, W Zhang, R Zhang, R Tang Proceedings of the Thirty-First International Joint Conference on Artificial …, 2022 | 11 | 2022 |
| Context-aware reranking with utility maximization for recommendation Y Xi, W Liu, X Dai, R Tang, W Zhang, Q Liu, X He, Y Yu arXiv preprint arXiv:2110.09059, 2021 | 11 | 2021 |
| U-rank: Utility-oriented learning to rank with implicit feedback X Dai, J Hou, Q Liu, Y Xi, R Tang, W Zhang, X He, J Wang, Y Yu Proceedings of the 29th ACM international conference on information …, 2020 | 9 | 2020 |
| On-device integrated re-ranking with heterogeneous behavior modeling Y Xi, W Liu, Y Wang, R Tang, W Zhang, Y Zhu, R Zhang, Y Yu Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 4 | 2023 |
| Beyond relevance ranking: a general graph matching framework for utility-oriented learning to rank X Dai, Y Xi, W Zhang, Q Liu, R Tang, X He, J Hou, J Wang, Y Yu ACM Transactions on Information Systems (TOIS) 40 (2), 1-29, 2021 | 3 | 2021 |
| DisCo: Towards Harmonious Disentanglement and Collaboration between Tabular and Semantic Space for Recommendation K Du, J Chen, J Lin, Y Xi, H Wang, X Dai, B Chen, R Tang, W Zhang arXiv preprint arXiv:2406.00011, 2024 | | 2024 |
| ClickPrompt: CTR Models are Strong Prompt Generators for Adapting Language Models to CTR Prediction J Lin, B Chen, H Wang, Y Xi, Y Qu, X Dai, K Zhang, R Tang, Y Yu, ... Proceedings of the ACM on Web Conference 2024, 3319-3330, 2024 | | 2024 |
| Play to Your Strengths: Collaborative Intelligence of Conventional Recommender Models and Large Language Models Y Xi, W Liu, J Lin, C Wu, B Chen, R Tang, W Zhang, Y Yu arXiv preprint arXiv:2403.16378, 2024 | | 2024 |
| Utility-oriented Reranking with Counterfactual Context Y Xi, W Liu, X Dai, R Tang, Q Liu, W Zhang, Y Yu ACM Transactions on Knowledge Discovery from Data, 2024 | | 2024 |
| Personalized Diversification for Neural Re-ranking in Recommendation W Liu, Y Xi, J Qin, X Dai, R Tang, S Li, W Zhang, R Zhang 2023 IEEE 39th International Conference on Data Engineering (ICDE), 802-815, 2023 | | 2023 |
