Document-Level Translation is a machine translation approach that operates on entire documents as the primary unit of translation, distinguishing itself from sentence-level translation by incorporating cross-sentence contextual information to achieve global coherence and discourse-level accuracy.
63
Publications
2.8K
Citations
181
Authors
71
Institutions
Publications per year
2017–2026
42
Parents
Publications
63
Improving the Transformer Translation Model with Document-Level Context
Jiacheng Zhang, Huanbo Luan, Maosong Sun et al. · 2018 · 257 citations · Full text
Document-Level Machine Translation with Large Language Models
Longyue Wang, Chenyang Lyu, Tianbo Ji et al. · 2023 · 133 citations · Full text
1–5 of 63
Authors
181
- DX
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- LS
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- JT
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- MZ
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- CH
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1–5 of 181
Institutions
71
Soochow University
Suzhou, China
8 h-index
20 publications
1K citations
University of Edinburgh
Edinburgh, United Kingdom
3 h-index
11 publications
307 citations
University of Zurich
Zurich, Switzerland
3 h-index
3 publications
57 citations
Institute for Infocomm Research
Singapore, Singapore
3 h-index
5 publications
223 citations
Dublin City University
Dublin, Ireland
3 h-index
3 publications
168 citations
Uppsala University
Uppsala, Sweden
3 h-index
11 publications
522 citations
University of Sheffield
Sheffield, United Kingdom
3 h-index
7 publications
474 citations
Nanjing University
Nanjing, China
2 h-index
8 publications
491 citations
1–8 of 71
Venues
- arXiv (Cornell University)
Repository · 11 publications · 391 citations
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- Edinburgh Research Explorer (University of Edinburgh)
Repository · 2 publications · 58 citations
2
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- Edinburgh Research Explorer
Repository · 1 publications · 74 citations
1
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- ACM SIGOIS Bulletin
1 publications · 10 citations
1
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- Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Conference · 1 publications · 17 citations
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