| Text embeddings by weakly-supervised contrastive pre-training L Wang, N Yang, X Huang, B Jiao, L Yang, D Jiang, R Majumder, F Wei arXiv preprint arXiv:2212.03533, 2022 | 156 | 2022 |
| Simlm: Pre-training with representation bottleneck for dense passage retrieval L Wang, N Yang, X Huang, B Jiao, L Yang, D Jiang, R Majumder, F Wei arXiv preprint arXiv:2207.02578, 2022 | 59 | 2022 |
| Improving text embeddings with large language models L Wang, N Yang, X Huang, L Yang, R Majumder, F Wei arXiv preprint arXiv:2401.00368, 2023 | 34 | 2023 |
| Lexmae: Lexicon-bottlenecked pretraining for large-scale retrieval T Shen, X Geng, C Tao, C Xu, X Huang, B Jiao, L Yang, D Jiang arXiv preprint arXiv:2208.14754, 2022 | 28 | 2022 |
| Large Search Model: Redefining Search Stack in the Era of LLMs L Wang, N Yang, X Huang, L Yang, R Majumder, F Wei ACM SIGIR Forum 57 (2), 1-16, 2024 | 3 | 2024 |
| Effective and efficient query-aware snippet extraction for web search J Yi, F Wu, C Wu, X Huang, B Jiao, G Sun, X Xie arXiv preprint arXiv:2210.08809, 2022 | 3 | 2022 |
| Multilingual e5 text embeddings: A technical report L Wang, N Yang, X Huang, L Yang, R Majumder, F Wei arXiv preprint arXiv:2402.05672, 2024 | 2 | 2024 |
