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Le modèle Transformer: un « couteau suisse » pour le traitement automatique des langues
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In: Techniques de l'Ingenieur ; https://hal.archives-ouvertes.fr/hal-03619077 ; Techniques de l'Ingenieur, Techniques de l'ingénieur, 2022, ⟨10.51257/a-v1-in195⟩ ; https://www.techniques-ingenieur.fr/base-documentaire/innovation-th10/innovations-en-electronique-et-tic-42257210/transformer-des-reseaux-de-neurones-pour-le-traitement-automatique-des-langues-in195/ (2022)
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Investigating alignment interpretability for low-resource NMT
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In: ISSN: 0922-6567 ; EISSN: 1573-0573 ; Machine Translation ; https://hal.archives-ouvertes.fr/hal-03139744 ; Machine Translation, Springer Verlag, 2021, ⟨10.1007/s10590-020-09254-w⟩ (2021)
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Impact of Encoding and Segmentation Strategies on End-to-End Simultaneous Speech Translation
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In: INTERSPEECH 2021 ; https://hal.archives-ouvertes.fr/hal-03372487 ; INTERSPEECH 2021, Aug 2021, Brno, Czech Republic (2021)
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cushLEPOR uses LABSE distilled knowledge to improve correlation with human translation evaluations
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In: Erofeev, Gleb, Sorokina, Irina, Han, Lifeng orcid:0000-0002-3221-2185 and Gladkoff, Serge (2021) cushLEPOR uses LABSE distilled knowledge to improve correlation with human translation evaluations. In: Machine Translation Summit 2021, 16-20 Aug 2021, USA (online). (In Press) (2021)
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Meta-evaluation of machine translation evaluation methods
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In: Han, Lifeng orcid:0000-0002-3221-2185 (2021) Meta-evaluation of machine translation evaluation methods. In: Workshop on Informetric and Scientometric Research (SIG-MET), 23-24 Oct 2021, Online. (2021)
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BERT, mBERT, or BiBERT? A Study on Contextualized Embeddings for Neural Machine Translation ...
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Abstract:
Anthology paper link: https://aclanthology.org/2021.emnlp-main.534/ Abstract: The success of bidirectional encoders using masked language models, such as BERT, on numerous natural language processing tasks has prompted researchers to attempt to incorporate these pre-trained models into neural machine translation (NMT) systems. However, proposed methods for incorporating pre-trained models are non-trivial and mainly focus on BERT, which lacks a comparison of the impact that other pre-trained models may have on translation performance. In this paper, we demonstrate that simply using the output (contextualized embeddings) of a tailored and suitable bilingual pre-trained language model (dubbed BiBERT) as the input of the NMT encoder achieves state-of-the-art translation performance. Moreover, we also propose a stochastic layer selection approach and a concept of dual-directional translation model to ensure the sufficient utilization of contextualized embeddings. In the case of without using back translation, our ...
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Keyword:
Computational Linguistics; Language Models; Machine Learning; Machine Learning and Data Mining; Machine translation; Natural Language Processing
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URL: https://dx.doi.org/10.48448/j1py-kc88
https://underline.io/lecture/37793-bert,-mbert,-or-bibertquestion-a-study-on-contextualized-embeddings-for-neural-machine-translation
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Sinhala-English Code-mixed and Code-switched Data Classification ...
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Exploring Pre-Trained Transformers and Bilingual Transfer Learning for Arabic Coreference Resolution ...
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Comparing Feature-Engineering and Feature-Learning Approaches for Multilingual Translationese Classification ...
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UNKs Everywhere: Adapting Multilingual Language Models to New Scripts ...
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Role of Language Relatedness in Multilingual Fine-tuning of Language Models: A Case Study in Indo-Aryan Languages ...
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Wino-X: Multilingual Winograd Schemas for Commonsense Reasoning and Coreference Resolution ...
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ERNIE-M: Enhanced Multilingual Representation by Aligning Cross-lingual Semantics with Monolingual Corpora ...
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A Massively Multilingual Analysis of Cross-linguality in Shared Embedding Space ...
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Improved Multilingual Language Model Pretraining for Social Media Text via Translation Pair Prediction ...
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Don't Go Far Off: An Empirical Study on Neural Poetry Translation ...
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