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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 1201–1250 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
Improving Robustness of Neural Machine Translation with Multi-task LearningCode0
Panlingua-KMI MT System for Similar Language Translation Task at WMT 2019—0
Terminology-Aware Segmentation and Domain Feature for the WMT19 Biomedical Translation Task—0
Parallel Corpus Filtering Based on Fuzzy String Matching—0
Tilde's Machine Translation Systems for WMT 2019—0
NICT's Supervised Neural Machine Translation Systems for the WMT19 News Translation Task—0
A Test Suite and Manual Evaluation of Document-Level NMT at WMT19—0
IITP-MT System for Gujarati-English News Translation Task at WMT 2019—0
LIUM's Contributions to the WMT2019 News Translation Task: Data and Systems for German-French Language Pairs—0
The NiuTrans Machine Translation Systems for WMT19—0
DFKI-NMT Submission to the WMT19 News Translation Task—0
Incorporating Source Syntax into Transformer-Based Neural Machine Translation—0
JU-Saarland Submission to the WMT2019 English--Gujarati Translation Shared Task—0
Multi-Source Transformer for Kazakh-Russian-English Neural Machine Translation—0
The LAIX Systems in the BEA-2019 GEC Shared Task—0
English-Czech Systems in WMT19: Document-Level Transformer—0
Joey NMT: A Minimalist NMT Toolkit for NovicesCode0
MacNet: Transferring Knowledge from Machine Comprehension to Sequence-to-Sequence Models—0
Learning the Relation between Code Features and Code Transforms with Structured PredictionCode0
Structure-Invariant Testing for Machine TranslationCode1
Understanding Neural Machine Translation by Simplification: The Case of Encoder-free Models—0
Hierarchical Sequence to Sequence Voice Conversion with Limited Data—0
Massively Multilingual Neural Machine Translation in the Wild: Findings and Challenges—0
Modelling the Socialization of Creative Agents in a Master-Apprentice Setting: The Case of Movie Title Puns—0
Exploiting Out-of-Domain Parallel Data through Multilingual Transfer Learning for Low-Resource Neural Machine TranslationCode0
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