Results 31 to 40 of about 4,356,022 (346)
In-context Examples Selection for Machine Translation [PDF]
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]
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
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]
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]
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
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
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]
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
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]
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