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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 961–970 of 1773 papers

TitleStatusHype
Multi-Reward based Reinforcement Learning for Neural Machine Translation—0
Constraining the Transformer NMT Model with Heuristic Grid Beam Search—0
Translation vs Post-editing of NMT Output: Insights from the English-Greek language pair—0
Rewriter-Evaluator Framework for Neural Machine Translation—0
Target Conditioning for One-to-Many Generation—0
Softmax Tempering for Training Neural Machine Translation Models—0
Energy-Based Reranking: Improving Neural Machine Translation Using Energy-Based ModelsCode0
Long-Short Term Masking Transformer: A Simple but Effective Baseline for Document-level Neural Machine Translation—0
Code-switching pre-training for neural machine translation—0
Dissecting Lottery Ticket Transformers: Structural and Behavioral Study of Sparse Neural Machine Translation—0
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