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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

Showing 126150 of 1773 papers

TitleStatusHype
TM2T: Stochastic and Tokenized Modeling for the Reciprocal Generation of 3D Human Motions and TextsCode1
Nested Music Transformer: Sequentially Decoding Compound Tokens in Symbolic Music and Audio GenerationCode1
A Survey on Non-Autoregressive Generation for Neural Machine Translation and BeyondCode1
Asynchronous Bidirectional Decoding for Neural Machine TranslationCode1
A Template-based Method for Constrained Neural Machine TranslationCode1
Fast Nearest Neighbor Machine TranslationCode1
FFR v1.1: Fon-French Neural Machine TranslationCode1
Generating Lead Sheets with Affect: A Novel Conditional seq2seq FrameworkCode1
Go From the General to the Particular: Multi-Domain Translation with Domain Transformation NetworksCode1
Automatic Dialect Adaptation in Finnish and its Effect on Perceived CreativityCode1
Automatic Machine Translation Evaluation in Many Languages via Zero-Shot ParaphrasingCode1
AutoMoE: Heterogeneous Mixture-of-Experts with Adaptive Computation for Efficient Neural Machine TranslationCode1
A Sketch-Based Neural Model for Generating Commit Messages from DiffsCode1
A Large-Scale Study of Machine Translation in Turkic LanguagesCode1
BERT, mBERT, or BiBERT? A Study on Contextualized Embeddings for Neural Machine TranslationCode1
Improving Multilingual Translation by Representation and Gradient RegularizationCode1
Improving Neural Machine Translation Models with Monolingual DataCode1
BigVideo: A Large-scale Video Subtitle Translation Dataset for Multimodal Machine TranslationCode1
Bi-SimCut: A Simple Strategy for Boosting Neural Machine TranslationCode1
It's Easier to Translate out of English than into it: Measuring Neural Translation Difficulty by Cross-Mutual InformationCode1
JASS: Japanese-specific Sequence to Sequence Pre-training for Neural Machine TranslationCode1
A Survey of Deep Learning Techniques for Neural Machine TranslationCode1
Bridging the Domain Gaps in Context Representations for k-Nearest Neighbor Neural Machine TranslationCode1
Breaking the Representation Bottleneck of Chinese Characters: Neural Machine Translation with Stroke Sequence ModelingCode1
Towards Making the Most of Cross-Lingual Transfer for Zero-Shot Neural Machine TranslationCode1
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