Effective Approaches to Attention-based Neural Machine Translation [PDF]
Conference on Empirical Methods in Natural Language Processing, 2015 An attentional mechanism has lately been used to improve neural machine translation (NMT) by selectively focusing on parts of the source sentence during translation.
Thang Luong +2 more
semanticscholar +1 more source
Experts, Errors, and Context: A Large-Scale Study of Human Evaluation for Machine Translation [PDF]
Transactions of the Association for Computational Linguistics, 2021 Human evaluation of modern high-quality machine translation systems is a difficult problem, and there is increasing evidence that inadequate evaluation procedures can lead to erroneous conclusions.
Markus Freitag +5 more
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Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation [PDF]
Conference on Empirical Methods in Natural Language Processing, 2014 In this paper, we propose a novel neural network model called RNN Encoder‐ Decoder that consists of two recurrent neural networks (RNN). One RNN encodes a sequence of symbols into a fixedlength vector representation, and the other decodes the ...
Kyunghyun Cho +6 more
semanticscholar +1 more source
The unreasonable effectiveness of few-shot learning for machine translation [PDF]
International Conference on Machine Learning, 2023 We demonstrate the potential of few-shot translation systems, trained with unpaired language data, for both high and low-resource language pairs. We show that with only 5 examples of high-quality translation data shown at inference, a transformer decoder-
Xavier García +7 more
semanticscholar +1 more source
On the Properties of Neural Machine Translation: Encoder–Decoder Approaches [PDF]
SSST@EMNLP, 2014 Neural machine translation is a relatively new approach to statistical machine translation based purely on neural networks. The neural machine translation models often consist of an encoder and a decoder.
Kyunghyun Cho +3 more
semanticscholar +1 more source
CURE: Code-Aware Neural Machine Translation for Automatic Program Repair [PDF]
International Conference on Software Engineering, 2021 Automatic program repair (APR) is crucial to improve software reliability. Recently, neural machine translation (NMT) techniques have been used to automatically fix software bugs. While promising, these approaches have two major limitations. Their search
Nan Jiang, Thibaud Lutellier, Lin Tan
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THE COMPARATIVE ANALYSIS OF THE MACHINE TRANSLATION SYSTEMS OF ECONOMIC DISCOURSE (ON THE EXAMPLE OF FRENCH-UKRAINIAN LANGUAGE PAIRS) [PDF]
Vìsnik Dnìpropetrovsʹkogo Unìversitetu Ekonomìki ta Prava Imenì Alʹfreda Nobelâ: Serìâ Fìlologìčnì Nauki, 2019 The paper is devoted to the research of the comparative analysis of the machine translation systems of French-language economic discourse in Ukrainian, taking into account the growing tendencies in the foreign economic activity of domestic enterprises ...
Nataliia M. Sopyluk, Ilona O. Tsarenko
doaj +1 more source
Translation Mechanism of Neural Machine Algorithm for Online English Resources
Complexity, 2021 At the level of English resource vocabulary, due to the lack of vocabulary alignment structure, the translation of neural machine translation has the problem of unfaithfulness.
Yanping Ye
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Advance Research on Neural Machine Translation Integrating Linguistic Knowledge
Jisuanji kexue yu tansuo, 2021 Although neural machine translation has become the mainstream method and paradigm in the current research and application of machine translation, there are also some problems such as the fluent but not faithful of the translation results, difficult ...
GUO Wanghao, FAN Jiangwei, ZHANG Keliang
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In-context Examples Selection for Machine Translation [PDF]
Annual 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