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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 1201–1225 of 1773 papers

TitleStatusHype
Reference Network for Neural Machine Translation—0
Controllable Dual Skew Divergence Loss for Neural Machine Translation—0
Improving Neural Machine Translation with Pre-trained Representation—0
Recurrent Graph Syntax Encoder for Neural Machine Translation—0
Hard but Robust, Easy but Sensitive: How Encoder and Decoder Perform in Neural Machine Translation—0
The Transference Architecture for Automatic Post-Editing—0
Incorporating Word and Subword Units in Unsupervised Machine Translation Using Language Model Rescoring—0
Towards Making the Most of BERT in Neural Machine TranslationCode0
Adabot: Fault-Tolerant Java Decompiler—0
UdS Submission for the WMT 19 Automatic Post-Editing Task—0
A Test Suite and Manual Evaluation of Document-Level NMT at WMT19Code0
Exploring the Robustness of NMT Systems to Nonsensical Inputs—0
Retrosynthesis with Attention-Based NMT Model and Chemical Analysis of the "Wrong" Predictions—0
Translating Terminologies: A Comparative Examination of NMT and PBSMT Systems—0
When a `sport' is a person and other issues for NMT of novels—0
Monolingual backtranslation in a medical speech translation system for diagnostic interviews - a NMT approach—0
Does NMT make a difference when post-editing closely related languages? The case of Spanish-Catalan—0
Utilizing Monolingual Data in NMT for Similar Languages: Submission to Similar Language Translation Task—0
Huawei's NMT Systems for the WMT 2019 Biomedical Translation Task—0
NICT's Supervised Neural Machine Translation Systems for the WMT19 Translation Robustness Task—0
SOURCE: SOURce-Conditional Elmo-style Model for Machine Translation Quality Estimation—0
NICT's Machine Translation Systems for the WMT19 Similar Language Translation Task—0
Effort-Aware Neural Automatic Post-Editing—0
The MuCoW Test Suite at WMT 2019: Automatically Harvested Multilingual Contrastive Word Sense Disambiguation Test Sets for Machine TranslationCode1
Neural Machine Translation: Hindi-Nepali—0
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