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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 451–500 of 1773 papers

TitleStatusHype
Chunk-Based Bi-Scale Decoder for Neural Machine TranslationCode0
Stronger Baselines for Trustable Results in Neural Machine TranslationCode0
BPE beyond Word Boundary: How NOT to use Multi Word Expressions in Neural Machine TranslationCode0
Domain Generalisation of NMT: Fusing Adapters with Leave-One-Domain-Out TrainingCode0
Synthetic and Natural Noise Both Break Neural Machine TranslationCode0
Domain Robustness in Neural Machine TranslationCode0
Exploiting Social Media Content for Self-Supervised Style TransferCode0
As Easy as 1, 2, 3: Behavioural Testing of NMT Systems for Numerical TranslationCode0
Exploring Paracrawl for Document-level Neural Machine TranslationCode0
Don't Overlook the Grammatical Gender: Bias Evaluation for Hindi-English Machine TranslationCode0
Doubly-Trained Adversarial Data Augmentation for Neural Machine TranslationCode0
The eBible Corpus: Data and Model Benchmarks for Bible Translation for Low-Resource LanguagesCode0
Examining the Tip of the Iceberg: A Data Set for Idiom TranslationCode0
DTMT: A Novel Deep Transition Architecture for Neural Machine TranslationCode0
Are We Paying Attention to Her? Investigating Gender Disambiguation and Attention in Machine TranslationCode0
Explicit Sentence Compression for Neural Machine TranslationCode0
Ensembling Factored Neural Machine Translation Models for Automatic Post-Editing and Quality EstimationCode0
Exploiting Cross-Sentence Context for Neural Machine TranslationCode0
Bridging the Gap between Training and Inference: Multi-Candidate Optimization for Diverse Neural Machine TranslationCode0
Dynamic Data Selection and Weighting for Iterative Back-TranslationCode0
Dynamic Data Selection for Neural Machine TranslationCode0
Exploring Recombination for Efficient Decoding of Neural Machine TranslationCode0
Enhanced Neural Machine Translation by Learning from DraftCode0
A Retrieve-and-Rewrite Initialization Method for Unsupervised Machine TranslationCode0
Enhancing Assamese NLP Capabilities: Introducing a Centralized Dataset RepositoryCode0
Character-level Chinese-English Translation through ASCII EncodingCode0
Byte-based Multilingual NMT for Endangered LanguagesCode0
Easy Guided Decoding in Providing Suggestions for Interactive Machine TranslationCode0
Energy-Based Reranking: Improving Neural Machine Translation Using Energy-Based ModelsCode0
English-Japanese Neural Machine Translation with Encoder-Decoder-ReconstructorCode0
Enhancing Low-Resource NMT with a Multilingual Encoder and Knowledge Distillation: A Case StudyCode0
Benchmarking Machine Translation with Cultural AwarenessCode0
Are Character-level Translations Worth the Wait? Comparing ByT5 and mT5 for Machine TranslationCode0
Encoder-Decoder Shift-Reduce Syntactic ParsingCode0
Effective Cross-lingual Transfer of Neural Machine Translation Models without Shared VocabulariesCode0
Incorporating Chinese Radicals Into Neural Machine Translation: Deeper Than Character LevelCode0
CCMatrix: Mining Billions of High-Quality Parallel Sentences on the WEBCode0
Towards User-Driven Neural Machine TranslationCode0
Training Deeper Neural Machine Translation Models with Transparent AttentionCode0
Efficient Cluster-Based k-Nearest-Neighbor Machine TranslationCode0
TransFool: An Adversarial Attack against Neural Machine Translation ModelsCode0
Efficient k-Nearest-Neighbor Machine Translation with Dynamic RetrievalCode0
Translate, then Parse! A strong baseline for Cross-Lingual AMR ParsingCode0
Translating Pro-Drop Languages with Reconstruction ModelsCode0
End-to-End Training for Back-Translation with Categorical Reparameterization TrickCode0
Enhancing Neural Machine Translation with Semantic UnitsCode0
Unsupervised Neural Machine TranslationCode0
Unsupervised Neural Machine Translation with SMT as Posterior RegularizationCode0
Exploring Unsupervised Pretraining Objectives for Machine TranslationCode0
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine TranslationCode0
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