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The recent MSMARCO passage retrieval collection has allowed researchers to develop highly tuned retrieval systems.
A new measure of rank correlation
M. G. Kendall · 1938
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A weighted Kendall’s tau statistic
G. S. Shieh · 1998
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Building a filtering test collection for TREC 2002
I. Soboroff and S. Robertson · 2003
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Forming test collections with no system pooling
M. Sanderson and H. Joho · 2004
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Semiautomatic evaluation of retrieval systems using document similarities
B. Carterette and J. Allan · 2007
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Query by document
Y. Yang, N. Bansal, W. Dakka, P. Ipeirotis, N. Koudas, and D. Papadias · 2009
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Test collection based evaluation of information retrieval systems
M. Sanderson · 2010
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A weighted correlation index for rankings with ties
S. Vigna · 2015
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MS MARCO: A human generated MAchine Reading COmprehension dataset
T. Nguyen, M. Rosenberg, X. Song, J. Gao, S. Tiwary, R. Majumder, and L. Deng · 2016
Cited alongside, same era.
Retrieval consistency in the presence of query variations
P. Bailey, A. Moffat, F. Scholer, and P. Thomas · 2017
Cited alongside, same era.
Learning to match using local and distributed representations of text for web search
B. Mitra, F. Diaz, and N. Craswell · 2017
Cited alongside, same era.
Anserini: Reproducible ranking baselines using Lucene
P. Yang, H. Fang, and J. Lin · 2018
Cited alongside, same era.
Learning a better negative sampling policy with deep neural networks for search
D. Cohen, S. M. Jordan, and W. B. Croft · 2019
Cited alongside, same era.
PISA: Performant indexes and search for academia
A. Mallia, M. Siedlaczek, J. Mackenzie, and T. Suel · 2019
Efficiency implications of term weighting for passage retrieval
J. Mackenzie, Z. Dai, L. Gallagher, and J. Callan · 2020
Later among the works it cites.
Shallow pooling for sparse labels
N. Arabzadeh, A. Vtyurina, X. Yan, and C. L. A. Clarke · 2021
Closest in time.
Billion-scale similarity search with GPUs
J. Johnson, M. Douze, and H. Jégou · 2021
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In-batch negatives for knowledge distillation with tightly-coupled teachers for dense retrieval
S.-C. Lin, J.-H. Yang, and J. Lin · 2021
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RocketQA: An optimized training approach to dense passage retrieval for open-domain question answering
Y. Qu, Y. Ding, J. Liu, K. Liu, R. Ren, W.-X. Zhao, D. Dong, H. Wu, and H. Wang · 2021
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Approximate nearest neighbor negative contrastive learning for dense text retrieval
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Cited alongside, same era.
Supporting interoperability between open-source search engines with the common index file format
J. Lin, J. Mackenzie, C. Kamphuis, C. Macdonald, A. Mallia, M. Siedlaczek, A. Trotman, and A. de Vries · 2020
Cited alongside, same era.
MS MARCO: Benchmarking ranking models in the large-data regime
N. Craswell, B. Mitra, E. Yilmaz, D. Campos, and J. Lin
Cited in the paper.
TREC deep learning track: Reusable test collections in the large data regime
N. Craswell, B. Mitra, E. Yilmaz, D. Campos, E. M. Voorhees, and I. Soboroff
Cited in the paper.
Pyserini: A Python toolkit for reproducible information retrieval research with sparse and dense representations
J. Lin, X. Ma, S.-C. Lin, J.-H. Yang, R. Pradeep, and R. Nogueira
Cited in the paper.
L. Xiong, C. Xiong, Y. Li, K.-F. Tang, J. Liu, P. N. Bennett, J. Ahmed, and A. Overwijk · 2021
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Optimizing dense retrieval model training with hard negatives
J. Zhan, J. Mao, Y. Liu, J. Guo, M. Zhang, and S. Ma · 2021
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