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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 1301–1350 of 1773 papers

TitleStatusHype
Semantic Diversity by Phonetics for Accurate and Robust Machine Translation—0
Revisiting Low-Resource Neural Machine Translation: A Case StudyCode0
Debiasing Word Embeddings Improves Multimodal Machine Translation—0
An Analysis of Source-Side Grammatical Errors in NMT—0
Corpus Augmentation by Sentence Segmentation for Low-Resource Neural Machine Translation—0
Target Conditioned Sampling: Optimizing Data Selection for Multilingual Neural Machine Translation—0
When a Good Translation is Wrong in Context: Context-Aware Machine Translation Improves on Deixis, Ellipsis, and Lexical CohesionCode1
Effective Cross-lingual Transfer of Neural Machine Translation Models without Shared VocabulariesCode0
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
Non-Parametric Adaptation for Neural Machine Translation—0
Reinforcement Learning based Curriculum Optimization for Neural Machine Translation—0
Massively Multilingual 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
An end-to-end Generative Retrieval Method for Sponsored Search Engine --Decoding Efficiently into a Closed Target Domain—0
Finding Sami Cognates with a Character-Based NMT Approach—0
Learning Efficient Lexically-Constrained Neural Machine Translation with External Memory—0
On Learning Meaningful Code Changes via Neural Machine Translation—0
Context in Neural Machine Translation: A Review of Models and Evaluations—0
Modeling Latent Sentence Structure in Neural Machine Translation—0
Unsupervised Neural Machine Translation with SMT as Posterior RegularizationCode0
ParaBank: Monolingual Bitext Generation and Sentential Paraphrasing via Lexically-constrained Neural Machine Translation—0
Learning to Refine Source Representations for Neural Machine Translation—0
What Is One Grain of Sand in the Desert? Analyzing Individual Neurons in Deep NLP ModelsCode1
How Much Does Tokenization Affect Neural Machine Translation?—0
DTMT: A Novel Deep Transition Architecture for Neural Machine TranslationCode0
SMT vs NMT: A Comparison over Hindi & Bengali Simple Sentences—0
Conditional Variational Autoencoder for Neural Machine Translation—0
SMT reranked NMT (2)—0
CUNI NMT System for WAT 2018 Translation Tasks—0
English-Myanmar NMT and SMT with Pre-ordering: NICT’s Machine Translation Systems at WAT-2018—0
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