| Feature generation by convolutional neural network for click-through rate prediction B Liu, R Tang, Y Chen, J Yu, H Guo, Y Zhang The World Wide Web Conference, 1119-1129, 2019 | 181 | 2019 |
| PAL: a position-bias aware learning framework for CTR prediction in live recommender systems H Guo, J Yu, Q Liu, R Tang, Y Zhang Proceedings of the 13th ACM Conference on Recommender Systems, 452-456, 2019 | 80 | 2019 |
| Field-aware probabilistic embedding neural network for CTR prediction W Liu, R Tang, J Li, J Yu, H Guo, X He, S Zhang Proceedings of the 12th ACM Conference on Recommender Systems, 412-416, 2018 | 23 | 2018 |
| End-to-end training of Multimodal Model and ranking Model X Deng, L Xu, X Li, J Yu, E Xue, Z Wang, D Zhang, Z Liu, G Zhou, Y Song, ... arXiv preprint arXiv:2404.06078, 2024 | 2 | 2024 |
| Recommendation model training method, selection probability prediction method, and apparatus GUO Huifeng, J Yu, Q Liu, R Tang, X He US Patent App. 17/691,843, 2022 | 2 | 2022 |
| QARM: Quantitative Alignment Multi-Modal Recommendation at Kuaishou X Luo, J Cao, T Sun, J Yu, R Huang, W Yuan, H Lin, Y Zheng, S Wang, ... arXiv preprint arXiv:2411.11739, 2024 | | 2024 |
| Recommendation method and apparatus J Yu, R Tang, D Zhenhua, Y Zhang, W Liu, L Qian US Patent 11,586,941, 2023 | | 2023 |
