Cross-encoder Re-ranking
Cross-Encoder Re-Ranking is a passage retrieval method that, as a member of the re-ranking models in semantic search, employs a bidirectional interaction architecture to jointly encode query-passage pairs and produce a refined relevance score through deep semantic fusion.
6
Publications
599
Citations
30
Authors
8
Institutions
Publications per year
2017–2026
6
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Scalable Zero-shot Entity Linking with Dense Entity Retrieval
Ledell Wu, Fabio Petroni, Martin Josifoski et al. · 2020 · 338 citations · Full text
Large Dual Encoders Are Generalizable Retrievers
Jianmo Ni, Chen Qu, Jing Lü et al. · 2022 · 149 citations · Full text
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University College London
London, United Kingdom
1 h-index
1 publications
338 citations
Leiden University
Leiden, The Netherlands
1 h-index
2 publications
24 citations
Apple (Germany)
Munich, Germany
1 h-index
11 publications
1.6K citations
École Polytechnique Fédérale de Lausanne
Lausanne, Switzerland
1 h-index
1 publications
338 citations
Meta (Israel)
Tel Aviv, Israel
1 h-index
4 publications
1.4K citations
Google (United States)
Mountain View, United States
1 h-index
11 publications
1.6K citations
Amsterdam University of the Arts
Amsterdam, The Netherlands
1 h-index
2 publications
24 citations

University of Amsterdam
Amsterdam, The Netherlands
1 h-index
2 publications
24 citations
1–8 of 8
Repository · 3 publications · 100 citations
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1 publications · 22 citations
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