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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 1151–1200 of 1773 papers

TitleStatusHype
KNU-HYUNDAI's NMT system for Scientific Paper and Patent Tasks onWAT 2019—0
Our Neural Machine Translation Systems for WAT 2019—0
Exploiting Multilingualism through Multistage Fine-Tuning for Low-Resource Neural Machine Translation—0
Exploiting Monolingual Data at Scale for Neural Machine Translation—0
NICT's participation to WAT 2019: Multilingualism and Multi-step Fine-Tuning for Low Resource NMT—0
Sarah's Participation in WAT 2019—0
Mixed Multi-Head Self-Attention for Neural Machine Translation—0
Adaptively Scheduled Multitask Learning: The Case of Low-Resource Neural Machine Translation—0
ESPnet How2 Speech Translation System for IWSLT 2019: Pre-training, Knowledge Distillation, and Going Deeper—0
Document-level Neural Machine Translation with Associated Memory Network—0
Adapting Multilingual Neural Machine Translation to Unseen LanguagesCode0
A Latent Morphology Model for Open-Vocabulary Neural Machine TranslationCode0
Findings of the Third Workshop on Neural Generation and Translation—0
Multitask Learning For Different Subword Segmentations In Neural Machine Translation—0
Promoting the Knowledge of Source Syntax in Transformer NMT Is Not Needed—0
Controlling the Output Length of Neural Machine Translation—0
Robust Neural Machine Translation for Clean and Noisy Speech Transcripts—0
A language processing algorithm for predicting tactical solutions to an operational planning problem under uncertainty—0
Controlling Utterance Length in NMT-based Word Segmentation with Attention—0
On the Importance of Word Boundaries in Character-level Neural Machine TranslationCode0
From the Paft to the Fiiture: a Fully Automatic NMT and Word Embeddings Method for OCR Post-CorrectionCode0
Novel Applications of Factored Neural Machine Translation—0
Improving Neural Machine Translation Robustness via Data Augmentation: Beyond Back Translation—0
Overcoming the Rare Word Problem for Low-Resource Language Pairs in Neural Machine Translation—0
On Leveraging the Visual Modality for Neural Machine Translation—0
Machine Translation for Machines: the Sentiment Classification Use Case—0
When and Why is Document-level Context Useful in Neural Machine Translation?Code0
Regressing Word and Sentence Embeddings for Regularization of Neural Machine Translation—0
Interrogating the Explanatory Power of Attention in Neural Machine TranslationCode0
On the use of BERT for Neural Machine Translation—0
Large-scale Pretraining for Neural Machine Translation with Tens of Billions of Sentence Pairs—0
Selecting Artificially-Generated Sentences for Fine-Tuning Neural Machine Translation—0
Self-Induced Curriculum Learning in Neural Machine Translation—0
Context Based Machine Translation With Recurrent Neural Network For English-Amharic Translation—0
Efficiently Reusing Old Models Across Languages via Transfer Learning—0
Self-attention based end-to-end Hindi-English Neural Machine Translation—0
Pivot-based Transfer Learning for Neural Machine Translation between Non-English Languages—0
Simple, Scalable Adaptation for Neural Machine Translation—0
Pointer-based Fusion of Bilingual Lexicons into Neural Machine TranslationCode0
Multilingual Neural Machine Translation for Zero-Resource LanguagesCode0
Beyond BLEU: Training Neural Machine Translation with Semantic SimilarityCode0
Neural Machine Translation with 4-Bit Precision and Beyond—0
CUNI System for the Building Educational Applications 2019 Shared Task: Grammatical Error Correction—0
Dynamic Fusion: Attentional Language Model for Neural Machine Translation—0
Getting Gender Right in Neural Machine Translation—0
Combining SMT and NMT Back-Translated Data for Efficient NMT—0
Multi-Granularity Self-Attention for Neural Machine Translation—0
Investigating Multilingual NMT Representations at Scale—0
Simpler and Faster Learning of Adaptive Policies for Simultaneous Translation—0
Multi-agent Learning for Neural Machine Translation—0
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