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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 71–80 of 1773 papers

TitleStatusHype
Language-Informed Beam Search Decoding for Multilingual Machine TranslationCode1
Simplifying Translations for Children: Iterative Simplification Considering Age of Acquisition with LLMsCode0
Enhancing AI-based Generation of Software Exploits with Contextual Information—0
Nested Music Transformer: Sequentially Decoding Compound Tokens in Symbolic Music and Audio GenerationCode1
The power of Prompts: Evaluating and Mitigating Gender Bias in MT with LLMs—0
Granularity is crucial when applying differential privacy to text: An investigation for neural machine translationCode0
Translate-and-Revise: Boosting Large Language Models for Constrained Translation—0
Segment-Based Interactive Machine Translation for Pre-trained Models—0
Enhancing Low-Resource NMT with a Multilingual Encoder and Knowledge Distillation: A Case StudyCode0
Rethinking Targeted Adversarial Attacks For Neural Machine TranslationCode0
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