| Neural machine translation of rare words with subword units R Sennrich arXiv preprint arXiv:1508.07909, 2015 | 9037 | 2015 |
| Improving neural machine translation models with monolingual data R Sennrich arXiv preprint arXiv:1511.06709, 2015 | 3157 | 2015 |
| Findings of the 2017 conference on machine translation (wmt17) O Bojar, R Chatterjee, C Federmann, Y Graham, B Haddow, S Huang, ... Association for Computational Linguistics, 2017 | 1465 | 2017 |
| Findings of the 2014 workshop on statistical machine translation O Bojar, C Buck, C Federmann, B Haddow, P Koehn, J Leveling, C Monz, ... Proceedings of the ninth workshop on statistical machine translation, 12-58, 2014 | 1309 | 2014 |
| Findings of the 2019 conference on machine translation (WMT19) L Barrault, O Bojar, MR Costa-Jussa, C Federmann, M Fishel, Y Graham, ... ACL, 2019 | 766 | 2019 |
| Edinburgh neural machine translation systems for WMT 16 R Sennrich, B Haddow, A Birch arXiv preprint arXiv:1606.02891, 2016 | 615 | 2016 |
| Overview of BioCreative II gene mention recognition L Smith, LK Tanabe, RJ Ando, CJ Kuo, IF Chung, CN Hsu, YS Lin, ... Genome biology 9, 1-19, 2008 | 554 | 2008 |
| Linguistic input features improve neural machine translation R Sennrich, B Haddow arXiv preprint arXiv:1606.02892, 2016 | 495 | 2016 |
| Nematus: a toolkit for neural machine translation R Sennrich, O Firat, K Cho, A Birch, B Haddow, J Hitschler, ... arXiv preprint arXiv:1703.04357, 2017 | 453 | 2017 |
| Controlling politeness in neural machine translation via side constraints R Sennrich, B Haddow, A Birch-Mayne 15th Annual Conference of the North American Chapter of the Association for …, 2016 | 363 | 2016 |
| Evaluating discourse phenomena in neural machine translation R Bawden, R Sennrich, A Birch, B Haddow arXiv preprint arXiv:1711.00513, 2017 | 318 | 2017 |
| ParaCrawl: Web-scale acquisition of parallel corpora M Bañón, P Chen, B Haddow, K Heafield, H Hoang, M Esplà-Gomis, ... Association for Computational Linguistics (ACL), 2020 | 265 | 2020 |
| Interactive assistance to human translators using statistical machine translation methods P Koehn, B Haddow Proceedings of MT Summit 12, 73-80, 2009 | 238 | 2009 |
| Recognising nested named entities in biomedical text B Alex, B Haddow, C Grover Biological, translational, and clinical language processing, 65-72, 2007 | 209 | 2007 |
| Prompting large language model for machine translation: A case study B Zhang, B Haddow, A Birch International Conference on Machine Learning, 41092-41110, 2023 | 201 | 2023 |
| The University of Edinburgh's neural MT systems for WMT17 R Sennrich, A Birch, A Currey, U Germann, B Haddow, K Heafield, ... arXiv preprint arXiv:1708.00726, 2017 | 201 | 2017 |
| Findings of the 2021 conference on machine translation (WMT21) F Akhbardeh, A Arkhangorodsky, M Biesialska, O Bojar, R Chatterjee, ... Proceedings of the sixth conference on machine translation, 1-88, 2021 | 191 | 2021 |
| Findings of the 2022 conference on machine translation (WMT22) T Kocmi, R Bawden, O Bojar, A Dvorkovich, C Federmann, M Fishel, ... Proceedings of the Seventh Conference on Machine Translation (WMT), 1-45, 2022 | 173 | 2022 |
| Survey of low-resource machine translation B Haddow, R Bawden, AVM Barone, J Helcl, A Birch Computational Linguistics 48 (3), 673-732, 2022 | 161 | 2022 |
| Assisted curation: does text mining really help B Alex, C Grover, B Haddow, M Kabadjov, E Klein, M Matthews, ... Pac Symp Biocomput 5, 56-67, 2008 | 130 | 2008 |
Philipp KoehnProfessor, Johns Hopkins UniversityVerified email at jhu.edu
