| 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 | 849 | 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 | 791 | 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 | 407 | 2014 |
| Adaptively sparse transformers GM Correia, V Niculae, AFT Martins arXiv preprint arXiv:1909.00015, 2019 | 262 | 2019 |
| Sparse sequence-to-sequence models B Peters, V Niculae, AFT Martins arXiv preprint arXiv:1905.05702, 2019 | 239 | 2019 |
| 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 | 229 | 2009 |
| Universal Dependencies 1.2 J Nivre, Ž Agić, MJ Aranzabe, M Asahara, A Atutxa, M Ballesteros, J Bauer, ... Universal Dependencies Consortium, 2015 | 226 | 2015 |
| 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 | 226 | 2013 |
| Selective attention for context-aware neural machine translation S Maruf, AFT Martins, G Haffari arXiv preprint arXiv:1903.08788, 2019 | 197 | 2019 |
| 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 | 172 | 2022 |
| 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 | 171 | 2022 |
| 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 |
| OpenKiwi: An open source framework for quality estimation F Kepler, J Trénous, M Treviso, M Vera, AFT Martins arXiv preprint arXiv:1902.08646, 2019 | 146 | 2019 |
| 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 |
| 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 | 144 | 2021 |
| An augmented Lagrangian approach to constrained MAP inference. AFT Martins, MAT Figueiredo, PMQ Aguiar, NA Smith, EP Xing ICML 2, 2, 2011 | 141 | 2011 |
| Nonextensive Information Theoretic Kernels on Measures. AFT Martins, NA Smith, EP Xing, PMQ Aguiar, MAT Figueiredo Journal of Machine Learning Research 10 (4), 2009 | 139 | 2009 |
| Sparsemap: Differentiable sparse structured inference V Niculae, A Martins, M Blondel, C Cardie International Conference on Machine Learning, 3799-3808, 2018 | 135 | 2018 |
| Learning with fenchel-young losses M Blondel, AFT Martins, V Niculae Journal of Machine Learning Research 21 (35), 1-69, 2020 | 132 | 2020 |
