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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 1051–1100 of 1773 papers

TitleStatusHype
Guiding attention in Sequence-to-sequence models for Dialogue Act predictionCode0
Towards Making the Most of Context in Neural Machine TranslationCode1
A Survey of Deep Learning Techniques for Neural Machine TranslationCode1
Incorporating BERT into Neural Machine TranslationCode1
Neural Machine Translation with Joint RepresentationCode1
Translating Web Search Queries into Natural Language Questions—0
Neural Machine Translation System of Indic Languages -- An Attention based ApproachCode1
PMIndia -- A Collection of Parallel Corpora of Languages of IndiaCode1
Pre-training via Leveraging Assisting Languages and Data Selection for Neural Machine Translation—0
A Simple Baseline to Semi-Supervised Domain Adaptation for Machine TranslationCode1
Bi-Decoder Augmented Network for Neural Machine Translation—0
Learning to Multi-Task Learn for Better Neural Machine Translation—0
A Comprehensive Survey of Multilingual Neural Machine Translation—0
Text2Sign: Towards Sign Language Production Using Neural Machine Translation and Generative Adversarial Networks—0
Morphological Word Segmentation on Agglutinative Languages for Neural Machine Translation—0
Reproducible and Efficient Benchmarks for Hyperparameter Optimization of Neural Machine Translation Systems—0
Explicit Sentence Compression for Neural Machine TranslationCode0
Amharic-Arabic Neural Machine Translation—0
A Study of Multilingual Neural Machine Translation—0
Tag-less Back-Translation—0
Iterative Dual Domain Adaptation for Neural Machine Translation—0
Acquiring Knowledge from Pre-trained Model to Neural Machine Translation—0
Neural Machine Translation: A Review and SurveyCode0
Cross-lingual Pre-training Based Transfer for Zero-shot Neural Machine Translation—0
Merging External Bilingual Pairs into Neural Machine Translation—0
Language Modelling with NMT Query Translation for Amharic-Arabic Cross-Language Information Retrieval—0
Iterative Batch Back-Translation for Neural Machine Translation: A Conceptual Model—0
Neural Machine Translation with Explicit Phrase Alignment—0
Learning to Reuse Translations: Guiding Neural Machine Translation with Examples—0
Go From the General to the Particular: Multi-Domain Translation with Domain Transformation NetworksCode1
Character-based NMT with Transformer—0
Diversity by Phonetics and its Application in Neural Machine Translation—0
CCMatrix: Mining Billions of High-Quality Parallel Sentences on the WEBCode0
Language Model-Driven Unsupervised Neural Machine Translation—0
Translationese as a Language in "Multilingual" NMT—0
Pretrained Language Models for Document-Level Neural Machine Translation—0
Domain Robustness in Neural Machine TranslationCode0
A General Framework for Adaptation of Neural Machine Translation to Simultaneous Translation—0
SubCharacter Chinese-English Neural Machine Translation with Wubi encoding—0
Multi-Domain Neural Machine Translation with Word-Level Adaptive Layer-wise Domain MixingCode0
Using Interlinear Glosses as Pivot in Low-Resource Multilingual Machine Translation—0
Training Neural Machine Translation (NMT) Models using Tensor Train Decomposition on TensorFlow (T3F)—0
Data Diversification: A Simple Strategy For Neural Machine TranslationCode1
On Compositionality in Neural Machine Translation—0
Domain Adaptation of Document-Level NMT in IWSLT19—0
Efficient Bilingual Generalization from Neural Transduction Grammar Induction—0
OPPO NMT System for IWSLT 2019—0
CMU’s Machine Translation System for IWSLT 2019—0
ESPnet How2 Speech Translation System for IWSLT 2019: Pre-training, Knowledge Distillation, and Going Deeper—0
Lexical Micro-adaptation for Neural Machine Translation—0
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