| Beam search strategies for neural machine translation M Freitag, Y Al-Onaizan arXiv preprint arXiv:1702.01806, 2017 | 275 | 2017 |
| Fast domain adaptation for neural machine translation M Freitag, Y Al-Onaizan arXiv preprint arXiv:1612.06897, 2016 | 191 | 2016 |
| Experts, errors, and context: A large-scale study of human evaluation for machine translation M Freitag, G Foster, D Grangier, V Ratnakar, Q Tan, W Macherey Transactions of the Association for Computational Linguistics 9, 1460-1474, 2021 | 174 | 2021 |
| Palm 2 technical report R Anil, AM Dai, O Firat, M Johnson, D Lepikhin, A Passos, S Shakeri, ... arXiv preprint arXiv:2305.10403, 2023 | 126 | 2023 |
| Findings of the 2021 conference on machine translation (WMT21) A Farhad, A Arkady, B Magdalena, B Ondřej, C Rajen, C Vishrav, ... Proceedings of the Sixth Conference on Machine Translation, 1-88, 2021 | 119 | 2021 |
| Results of the WMT20 metrics shared task N Mathur, J Wei, M Freitag, Q Ma, O Bojar Proceedings of the Fifth Conference on Machine Translation, 688-725, 2020 | 111 | 2020 |
| Ensemble distillation for neural machine translation M Freitag, Y Al-Onaizan, B Sankaran arXiv preprint arXiv:1702.01802, 2017 | 100 | 2017 |
| Results of the WMT15 metrics shared task M Stanojević, A Kamran, P Koehn, O Bojar Proceedings of the Tenth Workshop on Statistical Machine Translation, 256-273, 2015 | 99 | 2015 |
| BLEU might be guilty but references are not innocent M Freitag, D Grangier, I Caswell arXiv preprint arXiv:2004.06063, 2020 | 97 | 2020 |
| Results of the WMT21 metrics shared task: Evaluating metrics with expert-based human evaluations on TED and news domain M Freitag, R Rei, N Mathur, C Lo, C Stewart, G Foster, A Lavie, O Bojar Proceedings of the Sixth Conference on Machine Translation, 733-774, 2021 | 90 | 2021 |
| Modeling punctuation prediction as machine translation S Peitz, M Freitag, A Mauser, H Ney Proceedings of the 8th International Workshop on Spoken Language Translation …, 2011 | 88 | 2011 |
| APE at scale and its implications on MT evaluation biases M Freitag, I Caswell, S Roy arXiv preprint arXiv:1904.04790, 2019 | 55 | 2019 |
| Unsupervised natural language generation with denoising autoencoders M Freitag, S Roy In Proceedings of the 2018 Conference on Empirical Methods in Natural …, 2018 | 53 | 2018 |
| Language models are multilingual chain-of-thought reasoners F Shi, M Suzgun, M Freitag, X Wang, S Srivats, S Vosoughi, HW Chung, ... arXiv preprint arXiv:2210.03057, 2022 | 52 | 2022 |
| Jane: Open source machine translation system combination M Freitag, M Huck, H Ney Proceedings of the Demonstrations at the 14th Conference of the European …, 2014 | 49 | 2014 |
| Jane 2: Open source phrase-based and hierarchical statistical machine translation J Wuebker, M Huck, S Peitz, M Nuhn, M Freitag, JT Peter, S Mansour, ... Proceedings of COLING 2012: Demonstration Papers, 483-492, 2012 | 48 | 2012 |
| Scaling laws for neural machine translation B Ghorbani, O Firat, M Freitag, A Bapna, M Krikun, X Garcia, C Chelba, ... arXiv preprint arXiv:2109.07740, 2021 | 47 | 2021 |
| Complete multilingual neural machine translation M Freitag, O Firat arXiv preprint arXiv:2010.10239, 2020 | 41 | 2020 |
| Results of WMT22 metrics shared task: Stop using BLEU–neural metrics are better and more robust M Freitag, R Rei, N Mathur, C Lo, C Stewart, E Avramidis, T Kocmi, ... Proceedings of the Seventh Conference on Machine Translation (WMT), 46-68, 2022 | 37 | 2022 |
| The RWTH system combination system for WMT 2011 G Leusch, M Freitag, H Ney Proceedings of the Sixth Workshop on Statistical Machine Translation, 152-158, 2011 | 35 | 2011 |
Hermann NeyRWTH Aachen University在 cs.rwth-aachen.de 的电子邮件经过验证
