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Rolf Jagerman
Rolf Jagerman
Google DeepMind
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Title
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Cited by
Year
Large language models are effective text rankers with pairwise ranking prompting
Z Qin, R Jagerman, K Hui, H Zhuang, J Wu, J Shen, T Liu, J Liu, D Metzler, ...
arXiv preprint arXiv:2306.17563, 2023
1002023
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
802019
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
662019
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
572023
Query expansion by prompting large language models
R Jagerman, H Zhuang, Z Qin, X Wang, M Bendersky
arXiv preprint arXiv:2305.03653, 2023
382023
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
31*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
292018
Safe exploration for optimizing contextual bandits
R Jagerman, I Markov, MD Rijke
ACM Transactions on Information Systems (TOIS) 38 (3), 1-23, 2020
192020
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
172017
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
162022
Accelerated Convergence for Counterfactual Learning to Rank
R Jagerman, M de Rijke
Proceedings of the 43rd International ACM SIGIR Conference on Research and …, 2020
142020
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
112022
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
112014
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
102017
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
9*2023
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
82021
Overview of TREC OpenSearch 2017.
R Jagerman, K Balog, P Schaer, J Schaible, N Tavakolpoursaleh, ...
TREC, 2017
62017
Query-level Ranker Specialization
R Jagerman, H Oosterhuis, M de Rijke
1st International Workshop on LEARning Next gEneration Rankers (LEARNER), 2017
42017
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
32023
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
12023
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Articles 1–20