| Supervised learning of universal sentence representations from natural language inference data A Conneau, D Kiela, H Schwenk, L Barrault, A Bordes arXiv preprint arXiv:1705.02364, 2017 | 2468 | 2017 |
| Very deep convolutional networks for text classification A Conneau, H Schwenk, L Barrault, Y Lecun arXiv preprint arXiv:1606.01781, 2016 | 1260 | 2016 |
| What you can cram into a single vector: Probing sentence embeddings for linguistic properties A Conneau, G Kruszewski, G Lample, L Barrault, M Baroni arXiv preprint arXiv:1805.01070, 2018 | 910 | 2018 |
| Findings of the 2019 conference on machine translation (WMT19) L Barrault, O Bojar, MR Costa-Jussa, C Federmann, M Fishel, Y Graham, ... ACL, 2019 | 695 | 2019 |
| On using monolingual corpora in neural machine translation C Gulcehre, O Firat, K Xu, K Cho, L Barrault, HC Lin, F Bougares, ... arXiv preprint arXiv:1503.03535, 2015 | 632 | 2015 |
| No Language Left Behind: Scaling Human-Centered Machine Translation T NLLB, MR Costa-jussà, J Cross, O Çelebi, M Elbayad, K Heafield, ... arXiv e-prints, arXiv: 2207.04672, 2022 | 394* | 2022 |
| How2: a large-scale dataset for multimodal language understanding R Sanabria, O Caglayan, S Palaskar, D Elliott, L Barrault, L Specia, ... arXiv preprint arXiv:1811.00347, 2018 | 257 | 2018 |
| Findings of the second shared task on multimodal machine translation and multilingual image description D Elliott, S Frank, L Barrault, F Bougares, L Specia arXiv preprint arXiv:1710.07177, 2017 | 234 | 2017 |
| Findings of the third shared task on multimodal machine translation L Barrault, F Bougares, L Specia, C Lala, D Elliott, S Frank Third Conference on Machine Translation (WMT18) 2, 308-327, 2018 | 160 | 2018 |
| Probing the need for visual context in multimodal machine translation O Caglayan, P Madhyastha, L Specia, L Barrault arXiv preprint arXiv:1903.08678, 2019 | 152 | 2019 |
| Active learning by acquiring contrastive examples K Margatina, G Vernikos, L Barrault, N Aletras arXiv preprint arXiv:2109.03764, 2021 | 131 | 2021 |
| LIUM-CVC submissions for WMT17 multimodal translation task O Caglayan, W Aransa, A Bardet, M García-Martínez, F Bougares, ... arXiv preprint arXiv:1707.04481, 2017 | 109 | 2017 |
| The matecat tool M Federico, N Bertoldi, M Cettolo, M Negri, M Turchi, M Trombetti, ... Proceedings of COLING 2014, the 25th International Conference on …, 2014 | 102 | 2014 |
| The IWSLT 2019 evaluation campaign N Jan, R Cattoni, S Sebastian, M Negri, M Turchi, S Elizabeth, S Ramon, ... Proceedings of the 16th International Workshop on Spoken Language …, 2019 | 99 | 2019 |
| Does multimodality help human and machine for translation and image captioning? O Caglayan, W Aransa, Y Wang, M Masana, M García-Martínez, ... arXiv preprint arXiv:1605.09186, 2016 | 90 | 2016 |
| Findings of the IWSLT 2022 Evaluation Campaign. A Anastasopoulos, L Barrault, L Bentivogli, MZ Boito, O Bojar, R Cattoni, ... Proceedings of the 19th International Conference on Spoken Language …, 2022 | 89 | 2022 |
| Multimodal attention for neural machine translation O Caglayan, L Barrault, F Bougares arXiv preprint arXiv:1609.03976, 2016 | 81 | 2016 |
| Nmtpy: A flexible toolkit for advanced neural machine translation systems O Caglayan, M García-Martínez, A Bardet, W Aransa, F Bougares, ... The Prague Bulletin of Mathematical Linguistics 109 (1), 2017 | 77 | 2017 |
| Factored neural machine translation architectures M García-Martínez, L Barrault, F Bougares Proceedings of the 13th International Conference on Spoken Language Translation, 2016 | 54 | 2016 |
| Introduction to the special issue on deep learning approaches for machine translation MR Costa-jussà, A Allauzen, L Barrault, K Cho, H Schwenk Computer Speech & Language 46, 367-373, 2017 | 47 | 2017 |
Holger SchwenkResearch scientist, Facebook, and professor of Computer ScienceVerified email at fb.com
