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NMT

Neural machine translation is an approach to machine translation that uses an artificial neural network to predict the likelihood of a sequence of words, typically modeling entire sentences in a single integrated model.

Papers

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Showing 601–625 of 1773 papers

TitleStatusHype
Language Relatedness and Lexical Closeness can help Improve Multilingual NMT: IITBombay@MultiIndicNMT WAT2021—0
Pre-training Methods for Neural Machine Translation—0
On the differences between BERT and MT encoder spaces and how to address them in translation tasks—0
Breaking the Corpus Bottleneck for Context-Aware Neural Machine Translation with Cross-Task Pre-training—0
When is Char Better Than Subword: A Systematic Study of Segmentation Algorithms for Neural Machine Translation—0
An Empirical Study on Adversarial Attack on NMT: Languages and Positions Matter—0
Point, Disambiguate and Copy: Incorporating Bilingual Dictionaries for Neural Machine Translation—0
Observing the Learning Curve of NMT Systems With Regard to Linguistic Phenomena—0
Modeling Task-Aware MIMO Cardinality for Efficient Multilingual Neural Machine Translation—0
Crafting Adversarial Examples for Neural Machine Translation—0
Continuous Language Generative FlowCode1
SemFace: Pre-training Encoder and Decoder with a Semantic Interface for Neural Machine Translation—0
Fast and Accurate Neural Machine Translation with Translation Memory—0
ChrEnTranslate: Cherokee-English Machine Translation Demo with Quality Estimation and Corrective FeedbackCode1
Revisiting Negation in Neural Machine TranslationCode0
The USYD-JD Speech Translation System for IWSLT 2021—0
Modeling Bilingual Conversational Characteristics for Neural Chat TranslationCode1
Modelling Latent Translations for Cross-Lingual TransferCode1
Integrating Unsupervised Data Generation into Self-Supervised Neural Machine Translation for Low-Resource Languages—0
As Easy as 1, 2, 3: Behavioural Testing of NMT Systems for Numerical TranslationCode0
On the Copying Behaviors of Pre-Training for Neural Machine TranslationCode0
On the Difficulty of Translating Free-Order Case-Marking LanguagesCode0
Generating Gender Augmented Data for NLP—0
Putting words into the system's mouth: A targeted attack on neural machine translation using monolingual data poisoningCode0
A Survey on Low-Resource Neural Machine Translation—0
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