| Large language models are effective text rankers with pairwise ranking prompting Z Qin, R Jagerman, K Hui, H Zhuang, J Wu, L Yan, J Shen, T Liu, J Liu, ... arXiv preprint arXiv:2306.17563, 2023 | 176 | 2023 |
| Rankt5: Fine-tuning t5 for text ranking with ranking losses H Zhuang, Z Qin, R Jagerman, K Hui, J Ma, J Lu, J Ni, X Wang, ... Proceedings of the 46th International ACM SIGIR Conference on Research and …, 2023 | 98 | 2023 |
| Query expansion by prompting large language models R Jagerman, H Zhuang, Z Qin, X Wang, M Bendersky arXiv preprint arXiv:2305.03653, 2023 | 84 | 2023 |
| To model or to intervene: A comparison of counterfactual and online learning to rank from user interactions R Jagerman, H Oosterhuis, M de Rijke Proceedings of the 42nd international ACM SIGIR conference on research and …, 2019 | 80 | 2019 |
| When people change their mind: Off-policy evaluation in non-stationary recommendation environments R Jagerman, I Markov, M de Rijke Proceedings of the twelfth ACM international conference on web search and …, 2019 | 71 | 2019 |
| Learning to rank in theory and practice: from gradient boosting to neural networks and unbiased learning C Lucchese, FM Nardini, RK Pasumarthi, S Bruch, M Bendersky, X Wang, ... Proceedings of the 42nd International ACM SIGIR Conference on Research and …, 2019 | 32* | 2019 |
| Opensearch: lessons learned from an online evaluation campaign R Jagerman, K Balog, MD Rijke Journal of Data and Information Quality (JDIQ) 10 (3), 1-15, 2018 | 28 | 2018 |
| Safe exploration for optimizing contextual bandits R Jagerman, I Markov, MD Rijke ACM Transactions on Information Systems (TOIS) 38 (3), 1-23, 2020 | 22 | 2020 |
| Computing Web-scale Topic Models using an Asynchronous Parameter Server R Jagerman, C Eickhoff, M de Rijke Proceedings of the 40th International ACM SIGIR Conference on Research and …, 2017 | 17 | 2017 |
| On optimizing top-k metrics for neural ranking models R Jagerman, Z Qin, X Wang, M Bendersky, M Najork Proceedings of the 45th International ACM SIGIR Conference on Research and …, 2022 | 16 | 2022 |
| Accelerated Convergence for Counterfactual Learning to Rank R Jagerman, M de Rijke Proceedings of the 43rd International ACM SIGIR Conference on Research and …, 2020 | 16 | 2020 |
| Rax: composable learning-to-rank using Jax R Jagerman, X Wang, H Zhuang, Z Qin, M Bendersky, M Najork Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 13 | 2022 |
| Regression compatible listwise objectives for calibrated ranking with binary relevance A Bai, R Jagerman, Z Qin, L Yan, P Kar, BR Lin, X Wang, M Bendersky, ... Proceedings of the 32nd ACM International Conference on Information and …, 2023 | 12 | 2023 |
| The fifteen year struggle of decentralizing privacy-enhancing technology R Jagerman, W Sabee, L Versluis, M de Vos, J Pouwelse arXiv preprint arXiv:1404.4818, 2014 | 12 | 2014 |
| Modeling Label Ambiguity for Neural List-Wise Learning to Rank R Jagerman, J Kiseleva, M de Rijke 2nd International Workshop on Neural Information Retrieval (Neu-IR), 2017 | 11 | 2017 |
| Bootstrapping recommendations at chrome web store Z Qin, H Zhuang, R Jagerman, X Qian, P Hu, DC Chen, X Wang, ... Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 9 | 2021 |
| Large Language Models are Effective Text Rankers with Pairwise Ranking Prompting. arXiv e-prints, Article Z Qin, R Jagerman, K Hui, H Zhuang, J Wu, J Shen, T Liu, J Liu, D Metzler, ... arXiv preprint arXiv:2306.17563, 2023 | 7 | 2023 |
| Overview of TREC OpenSearch 2017. R Jagerman, K Balog, P Schaer, J Schaible, N Tavakolpoursaleh, ... TREC, 2017 | 7 | 2017 |
| Generate, filter, and fuse: Query expansion via multi-step keyword generation for zero-shot neural rankers M Li, H Zhuang, K Hui, Z Qin, J Lin, R Jagerman, X Wang, M Bendersky arXiv preprint arXiv:2311.09175, 2023 | 5 | 2023 |
| RD-Suite: a benchmark for ranking distillation Z Qin, R Jagerman, RK Pasumarthi, H Zhuang, H Zhang, A Bai, K Hui, ... Advances in Neural Information Processing Systems 36, 2023 | 4 | 2023 |
Michael BenderskyGoogle DeepMindVerified email at google.com
