| From softmax to sparsemax: A sparse model of attention and multi-label classification A Martins, R Astudillo International conference on machine learning, 1614-1623, 2016 | 931 | 2016 |
| Marian: Fast neural machine translation in C++ M Junczys-Dowmunt, R Grundkiewicz, T Dwojak, H Hoang, K Heafield, ... arXiv preprint arXiv:1804.00344, 2018 | 848 | 2018 |
| A Survey on Automatic Text Summarization D Das, AFT Martins Language and Statistics II Course Project, LTI, CMU, 2007 | 737 | 2007 |
| Frame-semantic parsing D Das, D Chen, AFT Martins, N Schneider, NA Smith Computational linguistics 40 (1), 9-56, 2014 | 413 | 2014 |
| Adaptively sparse transformers GM Correia, V Niculae, AFT Martins arXiv preprint arXiv:1909.00015, 2019 | 292 | 2019 |
| Sparse sequence-to-sequence models B Peters, V Niculae, AFT Martins arXiv preprint arXiv:1905.05702, 2019 | 271 | 2019 |
| Universal Dependencies 2.2 J Nivre, M Abrams, Ž Agić, L Ahrenberg, L Antonsen, MJ Aranzabe, ... | 255 | 2018 |
| COMET-22: Unbabel-IST 2022 submission for the metrics shared task R Rei, JGC De Souza, D Alves, C Zerva, AC Farinha, T Glushkova, ... Proceedings of the Seventh Conference on Machine Translation (WMT), 578-585, 2022 | 247 | 2022 |
| Turning on the turbo: Fast third-order non-projective turbo parsers AFT Martins, MB Almeida, NA Smith Proceedings of the 51st Annual Meeting of the Association for Computational …, 2013 | 230 | 2013 |
| Concise integer linear programming formulations for dependency parsing AFT Martins, NA Smith, E Xing Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL …, 2009 | 228 | 2009 |
| 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 | 207 | 2022 |
| Selective attention for context-aware neural machine translation S Maruf, AFT Martins, G Haffari arXiv preprint arXiv:1903.08788, 2019 | 202 | 2019 |
| Turbo parsers: Dependency parsing by approximate variational inference AFT Martins, NA Smith, E Xing, P Aguiar, M Figueiredo Proceedings of the 2010 Conference on Empirical Methods in Natural Language …, 2010 | 167 | 2010 |
| Learning with fenchel-young losses M Blondel, AFT Martins, V Niculae Journal of Machine Learning Research 21 (35), 1-69, 2020 | 160 | 2020 |
| CometKiwi: IST-unbabel 2022 submission for the quality estimation shared task R Rei, M Treviso, NM Guerreiro, C Zerva, AC Farinha, C Maroti, ... arXiv preprint arXiv:2209.06243, 2022 | 156 | 2022 |
| OpenKiwi: An open source framework for quality estimation F Kepler, J Trénous, M Treviso, M Vera, AFT Martins arXiv preprint arXiv:1902.08646, 2019 | 155 | 2019 |
| Findings of the WMT 2021 shared task on quality estimation L Specia, F Blain, M Fomicheva, C Zerva, Z Li, V Chaudhary, AFT Martins Proceedings of the Sixth Conference on Machine Translation, 684-725, 2021 | 151 | 2021 |
| Sparsemap: Differentiable sparse structured inference V Niculae, A Martins, M Blondel, C Cardie International Conference on Machine Learning, 3799-3808, 2018 | 147 | 2018 |
| Summarization with a joint model for sentence extraction and compression AFT Martins, NA Smith Proceedings of the Workshop on Integer Linear Programming for Natural …, 2009 | 146 | 2009 |
| Hallucinations in large multilingual translation models NM Guerreiro, DM Alves, J Waldendorf, B Haddow, A Birch, P Colombo, ... Transactions of the Association for Computational Linguistics 11, 1500-1517, 2023 | 142 | 2023 |
