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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 321–330 of 1773 papers

TitleStatusHype
Learning to translate by learning to communicateCode0
Sockeye 3: Fast Neural Machine Translation with PyTorch—0
UM4: Unified Multilingual Multiple Teacher-Student Model for Zero-Resource Neural Machine TranslationCode0
TM2T: Stochastic and Tokenized Modeling for the Reciprocal Generation of 3D Human Motions and TextsCode1
Improving Neural Machine Translation with the Abstract Meaning Representation by Combining Graph and Sequence TransformersCode0
Reducing Disambiguation Biases in NMT by Leveraging Explicit Word Sense Information—0
Bridging the Gap between Training and Inference: Multi-Candidate Optimization for Diverse Neural Machine TranslationCode0
Unified NMT models for the Indian subcontinent, transcending script-barriers—0
Cross-Language Transfer of High-Quality Annotations: Combining Neural Machine Translation with Cross-Linguistic Span Alignment to Apply NER to Clinical Texts in a Low-Resource LanguageCode0
End-to-End Simultaneous Speech Translation with Pretraining and Distillation: Huawei Noah’s System for AutoSimTranS 2022—0
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