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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 1451–1500 of 1773 papers

TitleStatusHype
SwitchOut: an Efficient Data Augmentation Algorithm for Neural Machine Translation—0
Learning When to Concentrate or Divert Attention: Self-Adaptive Attention Temperature for Neural Machine TranslationCode0
Measuring Semantic Abstraction of Multilingual NMT with Paraphrase Recognition and Generation Tasks—0
Neural Machine Translation of Text from Non-Native SpeakersCode0
SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing—0
Regularizing Neural Machine Translation by Target-bidirectional Agreement—0
D-PAGE: Diverse Paraphrase Generation—0
Ancient-Modern Chinese Translation with a Large Training Dataset—0
Debugging Neural Machine TranslationsCode0
code2seq: Generating Sequences from Structured Representations of CodeCode0
Neural Machine Translation Incorporating Named Entity—0
KIT Lecture Translator: Multilingual Speech Translation with One-Shot Learning—0
Adaptive Weighting for Neural Machine TranslationCode0
Tailoring Neural Architectures for Translating from Morphologically Rich Languages—0
Improving Neural Machine Translation by Incorporating Hierarchical Subword Features—0
Neural Machine Translation with Decoding History Enhanced Attention—0
Incorporating Syntactic Uncertainty in Neural Machine Translation with a Forest-to-Sequence Model—0
Low-Latency Neural Speech Translation—0
Effective Parallel Corpus Mining using Bilingual Sentence Embeddings—0
Training Neural Machine Translation using Word Embedding-based Loss—0
NMT-based Cross-lingual Document Embeddings—0
Finding Better Subword Segmentation for Neural Machine TranslationCode0
Otem&Utem: Over- and Under-Translation Evaluation Metric for NMTCode0
Recurrent Stacking of Layers for Compact Neural Machine Translation Models—0
NMT-Keras: a Very Flexible Toolkit with a Focus on Interactive NMT and Online Learning—0
Testing Untestable Neural Machine Translation: An Industrial Case—0
Named-Entity Tagging and Domain adaptation for Better Customized Translation—0
Neural Machine Translation Techniques for Named Entity TransliterationCode0
A Deep Learning Based Approach to Transliteration—0
OpenNMT System Description for WNMT 2018: 800 words/sec on a single-core CPU—0
NICT Self-Training Approach to Neural Machine Translation at NMT-2018—0
Regularized Training Objective for Continued Training for Domain Adaptation in Neural Machine TranslationCode0
Learning Distributional Token Representations from Visual Features—0
Unsupervised Source Hierarchies for Low-Resource Neural Machine Translation—0
Moon IME: Neural-based Chinese Pinyin Aided Input Method with Customizable Association—0
How Much Attention Do You Need? A Granular Analysis of Neural Machine Translation Architectures—0
Forest-Based Neural Machine Translation—0
Are BLEU and Meaning Representation in Opposition?—0
SuperNMT: Neural Machine Translation with Semantic Supersenses and Syntactic Supertags—0
Adaptive Knowledge Sharing in Multi-Task Learning: Improving Low-Resource Neural Machine Translation—0
A Simple and Effective Approach to Coverage-Aware Neural Machine Translation—0
Neural Hidden Markov Model for Machine Translation—0
Neural Machine Translation with Key-Value Memory-Augmented Attention—0
Neural Machine Translation for Low Resource Languages using Bilingual Lexicon Induced from Comparable Corpora—0
On Adversarial Examples for Character-Level Neural Machine TranslationCode0
Learning from Chunk-based Feedback in Neural Machine Translation—0
A Comparison of Transformer and Recurrent Neural Networks on Multilingual Neural Machine Translation—0
Morphological and Language-Agnostic Word Segmentation for NMTCode0
An Evaluation of Neural Machine Translation Models on Historical Spelling NormalizationCode0
Fusing Recency into Neural Machine Translation with an Inter-Sentence Gate Model—0
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