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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 1026–1050 of 1773 papers

TitleStatusHype
Improved Neural Machine Translation using Side Information—0
Improved Zero-shot Neural Machine Translation via Ignoring Spurious Correlations—0
Improvement in Machine Translation with Generative Adversarial Networks—0
Improving Autoregressive NLP Tasks via Modular Linearized Attention—0
Improving Autoregressive NMT with Non-Autoregressive Model—0
Improving Character-based Decoding Using Target-Side Morphological Information for Neural Machine Translation—0
Improving Character-level Japanese-Chinese Neural Machine Translation with Radicals as an Additional Input Feature—0
Improving Context-aware Neural Machine Translation with Target-side Context—0
Improving Document-Level Neural Machine Translation with Domain Adaptation—0
Improving English to Sinhala Neural Machine Translation using Part-of-Speech Tag—0
Improving Japanese-to-English Neural Machine Translation by Paraphrasing the Target Language—0
Improving Long Context Document-Level Machine Translation—0
Improving Low-Resource NMT through Relevance Based Linguistic Features Incorporation—0
Improving Machine Translation of Rare and Unseen Word Senses—0
Improving Machine Translation with Phrase Pair Injection and Corpus Filtering—0
Improving Multilingual Sentence Embedding using Bi-directional Dual Encoder with Additive Margin Softmax—0
Improving Neural Machine Translation Robustness via Data Augmentation: Beyond Back Translation—0
Improving Neural Machine Translation by Incorporating Hierarchical Subword Features—0
Improving Neural Machine Translation by Achieving Knowledge Transfer with Sentence Alignment Learning—0
Improving Neural Machine Translation by Multi-Knowledge Integration with Prompting—0
Improving Neural Machine Translation on resource-limited pairs using auxiliary data of a third language—0
Improving Neural Machine Translation through Phrase-based Forced Decoding—0
From Fully Trained to Fully Random Embeddings: Improving Neural Machine Translation with Compact Word Embedding Tables—0
Improving Neural Machine Translation with Neural Syntactic Distance—0
Improving Neural Machine Translation with Soft Template Prediction—0
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