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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 1401–1450 of 1773 papers

TitleStatusHype
Our Neural Machine Translation Systems for WAT 2019—0
Overcoming the Rare Word Problem for Low-Resource Language Pairs in Neural Machine Translation—0
Panlingua-KMI MT System for Similar Language Translation Task at WMT 2019—0
ParaBank: Monolingual Bitext Generation and Sentential Paraphrasing via Lexically-constrained Neural Machine Translation—0
Parallel Attention Forcing for Machine Translation—0
Parallel Corpus Filtering Based on Fuzzy String Matching—0
Parallel sentences mining with transfer learning in an unsupervised setting—0
ParaPat: The Multi-Million Sentences Parallel Corpus of Patents Abstracts—0
Paraphrases as Foreign Languages in Multilingual Neural Machine Translation—0
ParMod: A Parallel and Modular Framework for Learning Non-Markovian Tasks—0
Passing Parser Uncertainty to the Transformer. Labeled Dependency Distributions for Neural Machine Translation.—0
Patching Leaks in the Charformer for Generative Tasks—0
Patent NMT integrated with Large Vocabulary Phrase Translation by SMT at WAT 2017—0
Phrase-Based \& Neural Unsupervised Machine Translation—0
Phrase-level Active Learning for Neural Machine Translation—0
PAEG: Phrase-level Adversarial Example Generation for Neural Machine Translation—0
PhraseOut: A Code Mixed Data Augmentation Method for MultilingualNeural Machine Tranlsation—0
Phrase Table as Recommendation Memory for Neural Machine Translation—0
Pivot-based Transfer Learning for Neural Machine Translation between Non-English Languages—0
Point, Disambiguate and Copy: Incorporating Bilingual Dictionaries for Neural Machine Translation—0
POMP: Probability-driven Meta-graph Prompter for LLMs in Low-resource Unsupervised Neural Machine Translation—0
PosEdiOn: Post-Editing Assessment in PythOn—0
POS-Tagging based Neural Machine Translation System for European Languages using Transformers—0
Post-editing Productivity with Neural Machine Translation: An Empirical Assessment of Speed and Quality in the Banking and Finance Domain—0
Practical Neural Machine Translation—0
Predicting Human Translation Difficulty with Neural Machine Translation—0
Predicting Target Language CCG Supertags Improves Neural Machine Translation—0
Prediction Difference Regularization against Perturbation for Neural Machine Translation—0
Pretrained Language Models and Backtranslation for English-Basque Biomedical Neural Machine Translation—0
Pretrained Language Models for Document-Level Neural Machine Translation—0
FGraDA: A Dataset and Benchmark for Fine-Grained Domain Adaptation in Machine TranslationCode0
Massive Exploration of Neural Machine Translation ArchitecturesCode0
Online Versus Offline NMT Quality: An In-depth Analysis on English-German and German-EnglishCode0
Finding Better Subword Segmentation for Neural Machine TranslationCode0
Finding Memo: Extractive Memorization in Constrained Sequence Generation TasksCode0
Context Gates for Neural Machine TranslationCode0
Tilde's Machine Translation Systems for WMT 2018Code0
Revisiting Negation in Neural Machine TranslationCode0
Context-aware Neural Machine Translation with Mini-batch EmbeddingCode0
Unsupervised Neural Machine Translation with Weight SharingCode0
On Optimal Transformer Depth for Low-Resource Language TranslationCode0
Revisiting NMT for Normalization of Early English LettersCode0
Syllable-Based Sequence-to-Sequence Speech Recognition with the Transformer in Mandarin ChineseCode0
Fine-grained Human Evaluation of Transformer and Recurrent Approaches to Neural Machine Translation for English-to-ChineseCode0
On Synthetic Data for Back TranslationCode0
Fine-Tuning MT systems for Robustness to Second-Language Speaker VariationsCode0
Synchronous Bidirectional Neural Machine TranslationCode0
First the worst: Finding better gender translations during beam searchCode0
Context-aware Neural Machine Translation for English-Japanese Business Scene DialoguesCode0
On the Complementarity between Pre-Training and Random-Initialization for Resource-Rich Machine TranslationCode0
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