| Neural machine translation of rare words with subword units R Sennrich, B Haddow, A Birch ACL, 1715-1725, 2016 | 10855 | 2016 |
| Improving neural machine translation models with monolingual data R Sennrich, B Haddow, A Birch ACL, 86-96, 2016 | 3589 | 2016 |
| Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned E Voita, D Talbot, F Moiseev, R Sennrich, I Titov ACL, 2019 | 1811 | 2019 |
| Root Mean Square Layer Normalization B Zhang, R Sennrich NeurIPS, 2019 | 1410 | 2019 |
| Edinburgh neural machine translation systems for wmt 16 R Sennrich, B Haddow, A Birch WMT, 371-376, 2016 | 653 | 2016 |
| Linguistic input features improve neural machine translation R Sennrich, B Haddow WMT, 83-91, 2016 | 535 | 2016 |
| Nematus: a toolkit for neural machine translation R Sennrich, O Firat, K Cho, A Birch, B Haddow, J Hitschler, ... EACL, 2017 | 469 | 2017 |
| Improving Massively Multilingual Neural Machine Translation and Zero-Shot Translation B Zhang, P Williams, I Titov, R Sennrich ACL, 2020 | 439 | 2020 |
| Has Machine Translation Achieved Human Parity? A Case for Document-level Evaluation S Läubli, R Sennrich, M Volk EMNLP, 2018 | 435 | 2018 |
| Controlling politeness in neural machine translation via side constraints R Sennrich, B Haddow, A Birch NAACL, 35-40, 2016 | 395 | 2016 |
| Why self-attention? a targeted evaluation of neural machine translation architectures G Tang, M Müller, A Rios, R Sennrich EMNLP, 2018 | 381 | 2018 |
| Context-Aware Neural Machine Translation Learns Anaphora Resolution E Voita, P Serdyukov, R Sennrich, I Titov ACL, 2018 | 374 | 2018 |
| Evaluating Discourse Phenomena in Neural Machine Translation R Bawden, R Sennrich, A Birch, B Haddow NAACL, 2018 | 343 | 2018 |
| Revisiting Low-Resource Neural Machine Translation: A Case Study R Sennrich, B Zhang ACL, 2019 | 317 | 2019 |
| Paraphrasing Revisited with Neural Machine Translation J Mallinson, R Sennrich, M Lapata EACL, 2017 | 290 | 2017 |
| When a Good Translation is Wrong in Context: Context-Aware Machine Translation Improves on Deixis, Ellipsis, and Lexical Cohesion E Voita, R Sennrich, I Titov ACL, 2019 | 278 | 2019 |
| A parallel corpus of Python functions and documentation strings for automated code documentation and code generation AV Miceli Barone, R Sennrich IJCNLP 2017, 2017 | 224 | 2017 |
| The Bottom-up Evolution of Representations in the Transformer: A Study with Machine Translation and Language Modeling Objectives E Voita, R Sennrich, I Titov EMNLP, 2019 | 216 | 2019 |
| The University of Edinburgh's Neural MT Systems for WMT17 R Sennrich, A Birch, A Currey, U Germann, B Haddow, K Heafield, ... WMT, 2017 | 207 | 2017 |
| How Grammatical is Character-level Neural Machine Translation? Assessing MT Quality with Contrastive Translation Pairs R Sennrich EACL, 2017 | 204 | 2017 |
Barry HaddowUniversity of EdinburghVerified email at inf.ed.ac.uk
