Zobrazeno 1 - 10
of 165
pro vyhledávání: '"François Yvon"'
Autor:
François Yvon
Publikováno v:
MediAzioni, Vol 39, Pp A17-A34 (2023)
Neural machine translation (NMT) systems have made tangible progress in recent years, making them usable for an increasing number of domains and language pairs. The development of neural systems is based on machine learning algorithms and requires la
Externí odkaz:
https://doaj.org/article/e2e244e52c214e5c9d1fd746022b1a8e
Publikováno v:
Transactions of the Association for Computational Linguistics, Vol 9, Pp 17-35 (2021)
AbstractWhen building machine translation systems, one often needs to make the best out of heterogeneous sets of parallel data in training, and to robustly handle inputs from unexpected domains in testing. This multi-domain scenario has attracted a l
Externí odkaz:
https://doaj.org/article/73a669e6e7db48679b3dc19578d47cc1
Autor:
François Yvon
Publikováno v:
Computational Linguistics, Vol 45, Iss 2, Pp 391-394 (2019)
Externí odkaz:
https://doaj.org/article/c3473d29cef6430bb36fa5098f0a6780
Publikováno v:
Computational Linguistics and Intelligent Text Processing ISBN: 9783031237928
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5b0803bc3328397f6236c02b7d7dd54c
https://doi.org/10.1007/978-3-031-23793-5_28
https://doi.org/10.1007/978-3-031-23793-5_28
Autor:
François Yvon
Publikováno v:
Human-Centered Artificial Intelligence ISBN: 9783031243486
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::df9c7f3b7ece7e5f0cd7ba69bf46c625
https://doi.org/10.1007/978-3-031-24349-3_6
https://doi.org/10.1007/978-3-031-24349-3_6
Publikováno v:
Transactions of the Association for Computational Linguistics
Transactions of the Association for Computational Linguistics, The MIT Press, 2021, 9, pp.17-35
Transactions of the Association for Computational Linguistics, The MIT Press, 2021, 9, pp.17-35. ⟨10.1162/tacl_a_00351⟩
Transactions of the Association for Computational Linguistics-Volum
Transactions of the Association for Computational Linguistics, 2021, 9, pp.17-35. ⟨10.1162/tacl_a_00351⟩
Transactions of the Association for Computational Linguistics, The MIT Press, 2021, 9, pp.17-35
Transactions of the Association for Computational Linguistics, The MIT Press, 2021, 9, pp.17-35. ⟨10.1162/tacl_a_00351⟩
Transactions of the Association for Computational Linguistics-Volum
Transactions of the Association for Computational Linguistics, 2021, 9, pp.17-35. ⟨10.1162/tacl_a_00351⟩
International audience; When building machine translation systems, one often needs to make the best out of heterogeneous sets of parallel data in training, and to robustly handle inputs from unexpected domains in testing. This multi-domain scenario h
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::401e8fa6088cf85639acf5a6341713a6
https://doi.org/10.1162/tacl_a_00351
https://doi.org/10.1162/tacl_a_00351
Publikováno v:
Proceedings of the 60th Annual Meeting of the Association for Computational LinguisticsVolume 1: Long Papers
Annual meeting of the Association for Computational Linguistics
Annual meeting of the Association for Computational Linguistics, Association for Computational Linguistics, May 2022, Dublin, Ireland
Annual meeting of the Association for Computational Linguistics
Annual meeting of the Association for Computational Linguistics, Association for Computational Linguistics, May 2022, Dublin, Ireland
International audience; Word and morpheme segmentation are fundamental steps of language documentation as they allow to discover lexical units in a language for which the lexicon is unknown. However, in most language documentation scenarios, linguist
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bf84735f3a352e6ccd4a26d4ffbe8f9c
https://hal.science/hal-03679416/file/2022.acl-long.510.pdf
https://hal.science/hal-03679416/file/2022.acl-long.510.pdf
Autor:
François YVON
Publikováno v:
Innovations technologiques.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::acc57696e5c3f2f4ba64b2a7aed068fa
https://doi.org/10.51257/a-v1-in195
https://doi.org/10.51257/a-v1-in195
Publikováno v:
Proceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022 )
13th Language Resources and Evaluation Conference (LREC)
13th Language Resources and Evaluation Conference (LREC), ELDA, Jun 2022, Marseille, France
HAL
13th Language Resources and Evaluation Conference (LREC)
13th Language Resources and Evaluation Conference (LREC), ELDA, Jun 2022, Marseille, France
HAL
Subtitles appear on screen as short pieces of text, segmented based on formal constraints (length) and syntactic/semantic criteria. Subtitle segmentation can be evaluated with sequence segmentation metrics against a human reference. However, standard
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9737d0660d6c5e11ac9282da848a1090
Publikováno v:
Proceedings of the Fourth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP
Fourth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP
Fourth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, Association for computational linguistics, Nov 2021, Punta Cana, Dominica
BlackBoxNLP 2021
BlackBoxNLP 2021, Nov 2021, Punta Cana, Dominican Republic
HAL
Fourth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP
Fourth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, Association for computational linguistics, Nov 2021, Punta Cana, Dominica
BlackBoxNLP 2021
BlackBoxNLP 2021, Nov 2021, Punta Cana, Dominican Republic
HAL
This paper aims at identifying the information flow in state-of-the-art machine translation systems, taking as example the transfer of gender when translating from French into English. Using a controlled set of examples, we experiment several ways to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::853198fddc7ef1c3fddc26c024bb71a9
https://hal.science/hal-03424174
https://hal.science/hal-03424174