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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 951–1000 of 1773 papers

TitleStatusHype
Tagged Back-translation Revisited: Why Does It Really Work?—0
Content Word Aware Neural Machine Translation—0
Translationese as a Language in ``Multilingual'' NMT—0
Addressing Posterior Collapse with Mutual Information for Improved Variational Neural Machine Translation—0
A Retrieve-and-Rewrite Initialization Method for Unsupervised Machine TranslationCode0
Modeling Word Formation in English--German Neural Machine Translation—0
Uncertainty-Aware Curriculum Learning for Neural Machine Translation—0
Modeling Baroque Two-Part Counterpoint with Neural Machine TranslationCode0
Learning Source Phrase Representations for Neural Machine Translation—0
AdvAug: Robust Adversarial Augmentation for Neural Machine Translation—0
Fine-grained Human Evaluation of Transformer and Recurrent Approaches to Neural Machine Translation for English-to-ChineseCode0
FFR v1.1: Fon-French Neural Machine TranslationCode1
An Augmented Translation Technique for low Resource language pair: Sanskrit to Hindi translation—0
HausaMT v1.0: Towards English-Hausa Neural Machine Translation—0
Universal Vector Neural Machine Translation With Effective Attention—0
Modeling Discourse Structure for Document-level Neural Machine Translation—0
Enhanced back-translation for low resource neural machine translation using self-training—0
Norm-Based Curriculum Learning for Neural Machine TranslationCode1
Online Versus Offline NMT Quality: An In-depth Analysis on English-German and German-EnglishCode0
Is 42 the Answer to Everything in Subtitling-oriented Speech Translation?—0
Neural Simultaneous Speech Translation Using Alignment-Based Chunking—0
Variational Neural Machine Translation with Normalizing Flows—0
The Unreasonable Volatility of Neural Machine Translation ModelsCode0
Character-level Transformer-based Neural Machine Translation—0
Is MAP Decoding All You Need? The Inadequacy of the Mode in Neural Machine Translation—0
Encodings of Source Syntax: Similarities in NMT Representations Across Target Languages—0
DiscreTalk: Text-to-Speech as a Machine Translation Problem—0
Leveraging Monolingual Data with Self-Supervision for Multilingual Neural Machine Translation—0
Neural Machine Translation for South Africa's Official Languages—0
Does Multi-Encoder Help? A Case Study on Context-Aware Neural Machine TranslationCode1
On Exposure Bias, Hallucination and Domain Shift in Neural Machine TranslationCode1
JASS: Japanese-specific Sequence to Sequence Pre-training for Neural Machine TranslationCode1
It's Easier to Translate out of English than into it: Measuring Neural Translation Difficulty by Cross-Mutual InformationCode1
Using Context in Neural Machine Translation Training Objectives—0
Evaluating Explanation Methods for Neural Machine Translation—0
On the Inference Calibration of Neural Machine TranslationCode1
A Comprehensive Survey of Grammar Error Correction—0
Mirror-Generative Neural Machine Translation—0
Neural Machine Translation with Universal Visual RepresentationCode1
Much Ado About Nothing -- Identification of Zero Copulas in Hungarian Using an NMT Model—0
Improving NMT Quality Using Terminology Injection—0
The Learnability of the Annotated Input in NMT Replicating (Vanmassenhove and Way, 2018) with OpenNMT—0
The Nunavut Hansard Inuktitut--English Parallel Corpus 3.0 with Preliminary Machine Translation Results—0
Linguistically Informed Hindi-English Neural Machine Translation—0
Literary Machine Translation under the Magnifying Glass: Assessing the Quality of an NMT-Translated Detective Novel on Document Level—0
NMT and PBSMT Error Analyses in English to Brazilian Portuguese Automatic Translations—0
Corpora for Document-Level Neural Machine Translation—0
Multilingual Neural Machine Translation involving Indian Languages—0
Benchmarking Neural and Statistical Machine Translation on Low-Resource African Languages—0
Being Generous with Sub-Words towards Small NMT Children—0
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