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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 1326–1350 of 1773 papers

TitleStatusHype
Synchronous Bidirectional Neural Machine TranslationCode0
Syntax-Enhanced Neural Machine Translation with Syntax-Aware Word Representations—0
A Parallel Corpus of Theses and Dissertations Abstracts—0
A Guider Network for Multi-Dual Learning—0
Neural Machine Translation with Recurrent Highway Networks—0
Assessing the Tolerance of Neural Machine Translation Systems Against Speech Recognition Errors—0
Dynamic Past and Future for Neural Machine TranslationCode0
Code-Switching for Enhancing NMT with Pre-Specified TranslationCode0
APE at Scale and its Implications on MT Evaluation Biases—0
Cross-Corpora Evaluation and Analysis of Grammatical Error Correction Models --- Is Single-Corpus Evaluation Enough?—0
Consistency by Agreement in Zero-shot Neural Machine TranslationCode0
Multimodal Machine Translation with Embedding PredictionCode0
Competence-based Curriculum Learning for Neural Machine TranslationCode0
Selective Attention for Context-aware Neural Machine TranslationCode0
The Missing Ingredient in Zero-Shot Neural Machine Translation—0
Calibration of Encoder Decoder Models for Neural Machine Translation—0
Reinforcement Learning based Curriculum Optimization for Neural Machine Translation—0
Massively Multilingual Neural Machine Translation—0
Non-Parametric Adaptation for Neural Machine Translation—0
Augmenting Neural Machine Translation with Knowledge GraphsCode0
OpenKiwi: An Open Source Framework for Quality EstimationCode0
Improving Multilingual Sentence Embedding using Bi-directional Dual Encoder with Additive Margin Softmax—0
Semantic Neural Machine Translation using AMRCode0
Multilingual Neural Machine Translation With Soft Decoupled EncodingCode0
An Effective Approach to Unsupervised Machine TranslationCode0
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