Significant Improvements over the State of the Art? A Case Study of the MS MARCO Document Ranking Leaderboard-Reference-Cited by-同舟云学术

Significant Improvements over the State of the Art? A Case Study of the MS MARCO Document Ranking Leaderboard

Published:2021-07-11 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval
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Author:

Lin Jimmy¹,Campos Daniel²,Craswell Nick³,Mitra Bhaskar⁴,Yilmaz Emine⁵

Affiliation:

1. University of Waterloo and Microsoft AI & Research, Waterloo, ON, Canada

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

3. Microsoft AI & Research, Seattle, WA, USA

4. Microsoft AI & Research and University College London, Montreal, PQ, Canada

5. University College London, London, United Kingdom

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3404835.3463034

Reference15 articles.

1. Learning user interaction models for predicting web search result preferences

2. Expected Search Length: A Single Measure of Retrieval Effectiveness Based on the Weak Ordering Action of Retrieval Systems;Cooper William S.;Journal of the American Society for Information Science,1968

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

4. TREC Deep Learning Track: Reusable Test Collections in the Large Data Regime

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