| Neural machine translation: A review F Stahlberg Journal of Artificial Intelligence Research 69, 343-418, 2020 | 232 | 2020 |
| On NMT search errors and model errors: Cat got your tongue? F Stahlberg, B Byrne arXiv preprint arXiv:1908.10090, 2019 | 131 | 2019 |
| Neural models of text normalization for speech applications H Zhang, R Sproat, AH Ng, F Stahlberg, X Peng, K Gorman, B Roark Computational Linguistics 45 (2), 293-337, 2019 | 97 | 2019 |
| Syntactically guided neural machine translation F Stahlberg, E Hasler, A Waite, B Byrne The 54th Annual Meeting of the Association for Computational Linguistics, 299, 2016 | 84 | 2016 |
| Simple fusion: Return of the language model F Stahlberg, J Cross, V Stoyanov arXiv preprint arXiv:1809.00125, 2018 | 73 | 2018 |
| Synthetic data generation for grammatical error correction with tagged corruption models F Stahlberg, S Kumar arXiv preprint arXiv:2105.13318, 2021 | 68 | 2021 |
| Seq2Edits: Sequence transduction using span-level edit operations F Stahlberg, S Kumar arXiv preprint arXiv:2009.11136, 2020 | 64 | 2020 |
| Source sentence simplification for statistical machine translation E Hasler, A de Gispert, F Stahlberg, A Waite, B Byrne Computer Speech & Language 45, 221-235, 2017 | 44 | 2017 |
| Neural machine translation by minimising the Bayes-risk with respect to syntactic translation lattices F Stahlberg, A de Gispert, E Hasler, B Byrne arXiv preprint arXiv:1612.03791, 2016 | 39 | 2016 |
| The QCRI recognition system for handwritten Arabic F Stahlberg, S Vogel Image Analysis and Processing—ICIAP 2015: 18th International Conference …, 2015 | 35 | 2015 |
| An operation sequence model for explainable neural machine translation F Stahlberg, D Saunders, B Byrne arXiv preprint arXiv:1808.09688, 2018 | 32 | 2018 |
| Word segmentation through cross-lingual word-to-phoneme alignment F Stahlberg, T Schlippe, S Vogel, T Schultz Spoken Language Technology Workshop (SLT), 85-90, 2012 | 30 | 2012 |
| Neural grammatical error correction with finite state transducers F Stahlberg, C Bryant, B Byrne arXiv preprint arXiv:1903.10625, 2019 | 28 | 2019 |
| Multi-representation ensembles and delayed SGD updates improve syntax-based NMT D Saunders, F Stahlberg, A De Gispert, B Byrne arXiv preprint arXiv:1805.00456, 2018 | 27 | 2018 |
| Domain adaptive inference for neural machine translation D Saunders, F Stahlberg, A de Gispert, B Byrne arXiv preprint arXiv:1906.00408, 2019 | 26 | 2019 |
| The university of cambridge's machine translation systems for WMT18 F Stahlberg, A de Gispert, B Byrne arXiv preprint arXiv:1808.09465, 2018 | 23 | 2018 |
| SGNMT--A Flexible NMT Decoding Platform for Quick Prototyping of New Models and Search Strategies F Stahlberg, E Hasler, D Saunders, B Byrne arXiv preprint arXiv:1707.06885, 2017 | 23 | 2017 |
| Neural and FST-based approaches to grammatical error correction Z Yuan, F Stahlberg, M Rei, B Byrne, H Yannakoudakis Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building …, 2019 | 22 | 2019 |
| Text generation with text-editing models E Malmi, Y Dong, J Mallinson, A Chuklin, J Adamek, D Mirylenka, ... arXiv preprint arXiv:2206.07043, 2022 | 19 | 2022 |
| Using context in neural machine translation training objectives D Saunders, F Stahlberg, B Byrne arXiv preprint arXiv:2005.01483, 2020 | 18 | 2020 |
Bill ByrneProfessor of Information Engineering, Cambridge UniversityVerified email at eng.cam.ac.uk
