Neural Machine Translation
Neural Machine Translation is a machine translation approach that employs deep neural networks to model and generate natural language translations in an end-to-end manner, distinguishing itself from traditional statistical or rule-based methods through its use of continuous representations and learned contextual embeddings.
2.3K
Publications
303.6K
Citations
4.1K
Authors
918
Institutions
Publications per year
2017–2026
2K
Parents
2.3K
DROPS (Schloss Dagstuhl – Leibniz Center for Informatics) · 2023 · 76.3K citations · Full text
Sequence to Sequence Learning with Neural Networks
Ilya Sutskever, Oriol Vinyals, Quoc V. Le · arXiv (Cornell University) · 2014 · 13.4K citations · Full text
Computing, Computer Science, French +14
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Google (United States)
Mountain View, United States
50 h-index
298 publications
130.6K citations

University of Edinburgh
Edinburgh, United Kingdom
40 h-index
193 publications
18.2K citations
Tencent (China)
Shenzhen, China
34 h-index
230 publications
9.1K citations
Carnegie Mellon University
Pittsburgh, United States
34 h-index
187 publications
11.2K citations
Tsinghua University
Beijing, China
33 h-index
89 publications
7.4K citations
Meta (Israel)
Tel Aviv, Israel
32 h-index
155 publications
19.6K citations
Microsoft Research (United Kingdom)
Cambridge, United Kingdom
30 h-index
129 publications
15.2K citations

National Institute of Information and Communications Technology
Tokyo, Japan
29 h-index
143 publications
6.8K citations
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Repository · 513 publications · 75.2K citations
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Conference · 78 publications · 5.6K citations
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TASLP · 28 publications · 954 citations
21
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TACL · 18 publications · 4.5K citations
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18 publications · 822 citations
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