MS MARCO: Benchmarking Ranking Models in the Large-Data Regime

Author:

Craswell Nick1,Mitra Bhaskar2,Yilmaz Emine3,Campos Daniel4,Lin Jimmy5

Affiliation:

1. Microsoft, Bellevue, WA, USA

2. Microsoft & University College London, Montreal, PQ, Canada

3. University College London, London, United Kingdom

4. University of Illinois at Urbana-Champaign, Urbana-Champaign, IL, USA

5. University of Waterloo & Microsoft, Waterloo, ON, Canada

Publisher

ACM

Cited by 26 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Dense Text Retrieval based on Pretrained Language Models: A Survey;ACM Transactions on Information Systems;2023-12-18

2. Annotating Data for Fine-Tuning a Neural Ranker? Current Active Learning Strategies are not Better than Random Selection;Proceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region;2023-11-26

3. LeCAR: Leveraging Context for Enhanced Automotive Specification Retrieval;2023 IEEE 24th International Conference on Information Reuse and Integration for Data Science (IRI);2023-08

4. The Role of Relevance in Fair Ranking;Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval;2023-07-18

5. MGeo: Multi-Modal Geographic Language Model Pre-Training;Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval;2023-07-18

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