Results 31 to 40 of about 4,356,022 (346)

In-context Examples Selection for Machine Translation [PDF]

open access: yesAnnual Meeting of the Association for Computational Linguistics, 2022
Large-scale generative models show an impressive ability to perform a wide range of Natural Language Processing (NLP) tasks using in-context learning, where a few examples are used to describe a task to the model.
Sweta Agrawal   +4 more
semanticscholar   +1 more source

BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension [PDF]

open access: yesAnnual Meeting of the Association for Computational Linguistics, 2019
We present BART, a denoising autoencoder for pretraining sequence-to-sequence models. BART is trained by (1) corrupting text with an arbitrary noising function, and (2) learning a model to reconstruct the original text.
M. Lewis   +7 more
semanticscholar   +1 more source

Findings of the 2023 Conference on Machine Translation (WMT23): LLMs Are Here but Not Quite There Yet

open access: yesConference on Machine Translation, 2023
This paper presents the results of the General Machine Translation Task organised as part of the 2023 Conference on Machine Translation (WMT). In the general MT task, participants were asked to build machine translation systems for any of 8 language ...
Tom Kocmi   +20 more
semanticscholar   +1 more source

A Survey on Non-Autoregressive Generation for Neural Machine Translation and Beyond [PDF]

open access: yesIEEE Transactions on Pattern Analysis and Machine Intelligence, 2022
Non-autoregressive (NAR) generation, which is first proposed in neural machine translation (NMT) to speed up inference, has attracted much attention in both machine learning and natural language processing communities.
Yisheng Xiao   +6 more
semanticscholar   +1 more source

Neural Machine Translation for Low-resource Languages: A Survey [PDF]

open access: yesACM Computing Surveys, 2021
Neural Machine Translation (NMT) has seen tremendous growth in the last ten years since the early 2000s and has already entered a mature phase. While considered the most widely used solution for Machine Translation, its performance on low-resource ...
Surangika Ranathunga   +5 more
semanticscholar   +1 more source

PROBLEMS OF PSYCHOLOGICAL SCIENTISIC TEXTS MACHINE TRANSLATION ON THE MATERIAL OF AN INFORMATIONAL BROCHURE

open access: yesSovremennye Issledovaniâ Socialʹnyh Problem, 2022
The article is devoted to the analysis of the psychological scientific text machine translation (from the English language to the Russian one). On the material of the Russian machine translation of an informational brochure, potential difficulties were ...
Ksenia V. Antaeva, Yulia S. Elagina
doaj   +1 more source

Machine Translation with Large Language Models: Prompting, Few-shot Learning, and Fine-tuning with QLoRA

open access: yesConference on Machine Translation, 2023
While large language models have made remarkable advancements in natural language generation, their potential in machine translation, especially when fine-tuned, remains under-explored.
Xuan Zhang   +3 more
semanticscholar   +1 more source

Creativity in translation: machine translation as a constraint for literary texts [PDF]

open access: yesTranslation Spaces, 2022
This article presents the results of a study involving the translation of a short story by Kurt Vonnegut from English to Catalan and Dutch using three modalities: machine-translation (MT), post-editing (PE) and translation without aid (HT).
Ana Guerberof Arenas, Antonio Toral
semanticscholar   +1 more source

Evaluation of English–Slovak Neural and Statistical Machine Translation

open access: yesApplied Sciences, 2021
This study is focused on the comparison of phrase-based statistical machine translation (SMT) systems and neural machine translation (NMT) systems using automatic metrics for translation quality evaluation for the language pair of English and Slovak.
Lucia Benkova   +3 more
doaj   +1 more source

Contrastive Learning for Many-to-many Multilingual Neural Machine Translation [PDF]

open access: yesAnnual Meeting of the Association for Computational Linguistics, 2021
Existing multilingual machine translation approaches mainly focus on English-centric directions, while the non-English directions still lag behind. In this work, we aim to build a many-to-many translation system with an emphasis on the quality of non ...
Xiao Pan   +3 more
semanticscholar   +1 more source

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