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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 851–875 of 1773 papers

TitleStatusHype
Language Model-Driven Unsupervised Neural Machine Translation—0
Language Modeling, Lexical Translation, Reordering: The Training Process of NMT through the Lens of Classical SMT—0
Language Modelling with NMT Query Translation for Amharic-Arabic Cross-Language Information Retrieval—0
Language Models are Good Translators—0
Language Portability Strategies for Open-domain Dialogue with Pre-trained Language Models from High to Low Resource Languages—0
Language Relatedness and Lexical Closeness can help Improve Multilingual NMT: IITBombay@MultiIndicNMT WAT2021—0
Evaluation of NMT-Assisted Grammar Transfer for a Multi-Language Configurable Data-to-Text System—0
Large-scale Pretraining for Neural Machine Translation with Tens of Billions of Sentence Pairs—0
Latent Part-of-Speech Sequences for Neural Machine Translation—0
Latest Development in the FoTran Project – Scaling Up Language Coverage in Neural Machine Translation Using Distributed Training with Language-Specific Components—0
Lattice-Based Recurrent Neural Network Encoders for Neural Machine Translation—0
Lattice-Based Transformer Encoder for Neural Machine Translation—0
Layer-Wise Coordination between Encoder and Decoder for Neural Machine Translation—0
Evaluating the usefulness of neural machine translation for the Polish translators in the European Commission—0
Learning Contextualized Sentence Representations for Document-Level Neural Machine Translation—0
Learning Distributional Token Representations from Visual Features—0
Evaluating the Supervised and Zero-shot Performance of Multi-lingual Translation Models—0
Learning Efficient Lexically-Constrained Neural Machine Translation with External Memory—0
Learning Feature Weights using Reward Modeling for Denoising Parallel Corpora—0
Learning from Chunk-based Feedback in Neural Machine Translation—0
Evaluating the Performance of Back-translation for Low Resource English-Marathi Language Pair: CFILT-IITBombay @ LoResMT 2021—0
Learning How to Translate North Korean through South Korean—0
C-NMT: A Collaborative Inference Framework for Neural Machine Translation—0
A Simple and General Strategy for Referential Problem in Low-Resource Neural Machine Translation—0
Linguistically Motivated Vocabulary Reduction for Neural Machine Translation from Turkish to English—0
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