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Unsupervised Word embedding Alignment in the biomedical domain ; Alignement non supervisé d'embeddings de mots dans le domaine biomédical
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In: CIFSD - Conférence Internationale Francophone sur la Science des Données ; https://hal.archives-ouvertes.fr/hal-03259987 ; CIFSD - Conférence Internationale Francophone sur la Science des Données, Jun 2021, Marseille/Virtuel, France (2021)
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Models of diachronic semantic change using word embeddings ; Modèles diachroniques à base de plongements de mot pour l'analyse du changement sémantique
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In: https://tel.archives-ouvertes.fr/tel-03199801 ; Document and Text Processing. Université Paris-Saclay, 2021. English. ⟨NNT : 2021UPASG006⟩ (2021)
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Multilingual neural architectures for natural language processing ; Architectures neuronales multilingues pour le traitement automatique des langues naturelles
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In: https://tel.archives-ouvertes.fr/tel-03199494 ; Informatique et langage [cs.CL]. Université du Maine, 2021. Français. ⟨NNT : 2021LEMA1002⟩ (2021)
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Écrire en langues. Entre traduction automatique et hégémonie globish, le multilinguisme comme horizon réaliste pour les revues de SHS
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In: ISSN: 2490-9424 ; Biens Symboliques = Symbolic Goods ; https://halshs.archives-ouvertes.fr/halshs-03481421 ; Biens Symboliques = Symbolic Goods, Presses Universitaires de Vincennes, A paraître (2021)
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Extraction and normalization of simple and structured entities in medical documents ; Extraction et normalisation d'entités simples et structurées dans les documents médicaux
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In: https://hal.archives-ouvertes.fr/tel-03624928 ; Document and Text Processing. Sorbonne Université, 2021. English (2021)
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Automatic sentence simplification using controllable and unsupervised methods ; Simplification automatique de phrases à l'aide de méthodes contrôlables et non supervisées
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In: https://tel.archives-ouvertes.fr/tel-03543971 ; Computation and Language [cs.CL]. Sorbonne Université, 2021. English. ⟨NNT : 2021SORUS265⟩ (2021)
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Graph Algorithms for Multiparallel Word Alignment
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In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing ; The 2021 Conference on Empirical Methods in Natural Language Processing ; https://hal.archives-ouvertes.fr/hal-03424044 ; The 2021 Conference on Empirical Methods in Natural Language Processing, Association for Computational Linguistics, Nov 2021, Punta Cana, Dominica ; https://2021.emnlp.org/ (2021)
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Au cœur de la terminologie du jeu vidéo. L’absence de ressources, frein majeur pour les traducteurs
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In: ISSN: 0395-773X ; EISSN: 2272-9992 ; Traduire ; https://hal.archives-ouvertes.fr/hal-03465992 ; Traduire, Société française des traducteurs, 2021, Des jeux et des mots (2021)
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Modéliser la perception des genres musicaux à travers différentes cultures à partir de ressources linguistiques
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In: Actes de la 28e Conférence sur le Traitement Automatique des Langues Naturelles. Volume 1 : conférence principale ; Traitement Automatique des Langues Naturelles ; https://hal.archives-ouvertes.fr/hal-03265881 ; Traitement Automatique des Langues Naturelles, 2021, Lille, France. pp.270-272 (2021)
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A Lexico-phonetic Comparison of Olukumi and Lukumi: A Procedure for Developing a Multilingual Dictionary
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In: Lexikos; Vol. 31 (2021); 214-233 ; 2224-0039 (2021)
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La ressource FAIRterm : entre pratique pédagogique et professionnalisation en traduction spécialisée ...
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La ressource FAIRterm : entre pratique pédagogique et professionnalisation en traduction spécialisée ...
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Traduire le droit international pénal ... : Du concept international de génocide à ses définitions nationales ...
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Les possibilités de DiCoEnviro en version frames comme ressource pour la traduction ...
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Criação de narrativas multilineares como ferramenta de aprendizagem das línguas estrangeiras no ensino superior em Portugal
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Cross language plagiarism detection with contextualized word embeddings ; Detecção de plágio multilíngue usando word embeddings contextualizadas
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Abstract:
Plagiarism is the use of someone else’s work without the proper acknowledgment and citation, being one of the most significant publishing issues in academia and science. A study conducted by CopyLeaks in 2020 showed that plagiarism increased by 10% after the transition to online classes during the COVID-19 pandemic. In some cases, authors may translate texts from another language and include them in their work. This more “sophisticated” behavior is known as cross-language plagiarism. In this work, we investigate methods that are used for cross-language plagiarism detection. Although some of the approaches developed until now use word embeddings as part of their pipelines, few explore contextualized word embeddings. Contextualized embeddings can help address fundamental characteristics of language such as polysemy and synonymy by taking into account the context in which a particular word occurs. Pre-trained multilingual models have shown outstanding performance in downstream natural language understanding tasks, such as sentence similarity and next sentence prediction. Motivated by these promising results in tasks related to plagiarism detection, we present a new proposal for cross-language plagiarism detection using pre-trained multilingual models with contextualized embeddings. Experiments performed on different datasets, such as PAN-PC-12, show that the proposed cross-language plagiarism detection using contextualized embeddings outperforms state-of-the-art models by 9% and 11% regarding plagdet results obtained for the English-Spanish and English-German language pairs. ; Plágio é o uso do trabalho de outra pessoa sem o devido reconhecimento e citação, sendo um dos maiores problemas editoriais da academia e da ciência. Um estudo realizado em 2020 pela CopyLeaks mostrou que o plágio aumentou em 10% após a transição para aulas online durante a pandemia da COVID-19. Em alguns casos, os autores podem traduzir textos de outro idioma e incluir em seus próprios trabalhos. Este comportamento mais “sofisticado” é conhecido como plágio multilíngue. Neste trabalho, investigamos métodos que são usados para a detecção do plágio multilíngue. Embora algumas das abordagens desenvolvidas até agora utilizem word embeddings como parte de seu pipeline, poucas delas exploram contexualized word embeddings. Contexualized word embeddings consideram características fundamentais da linguagem, como a polissemia, levando em conta o contexto no qual uma palavra em particular ocorre. Modelos multilíngues pré-treinados têm demonstrado grande desempenho em tarefas multilíngues, tais como similaridade de sentenças e predição de próxima sentença. Assim, com resultados promissores para tarefas relacionadas à detecção de plágio, apresentamos uma nova proposta para a detecção de plágio multilíngue utilizando modelos multilíngues pré-treinados com embeddings contextuais. Experimentos realizados em diferentes conjuntos de dados, como o PAN-PC-12, mostram que a detecção de plágio multilíngue utilizando modelos multilíngues pré-treinados com embeddings contextuais supera supera em 9% e 11% os modelos de última geração em relação aos resultados de plagdet obtidos para os pares de idiomas inglês-espanhol e inglês-alemão.
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Keyword:
BERT; Cross language information retrieval; Cross language plagiarism detection; Plágio; Recuperação de informação : multilíngue; Word embeddings
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URL: http://hdl.handle.net/10183/226141
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| 18 |
A vertente turística da tradução e da comunicação multilingue: o caso do Posto de Turismo de Braga
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| 19 |
Le identità multiple delle famiglie multilingue: processi sottesi tra linguaggio e identità culturale
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Le projet HYPAquitaine : une innovation disruptive?
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In: Journée d’étude : Les Humanités numériques : une transdiscipline historique ; https://hal.archives-ouvertes.fr/hal-03140701 ; Journée d’étude : Les Humanités numériques : une transdiscipline historique, Université de La Rochelle, Nov 2020, La Rochelle, France (2020)
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