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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 1–10 of 1773 papers

TitleStatusHype
Amplifying Pathological Detection in EEG Signaling Pathways through Cross-Dataset Transfer LearningCode3
Neural Speech Synthesis with Transformer NetworkCode2
Beyond Decoder-only: Large Language Models Can be Good Encoders for Machine TranslationCode1
MT-LENS: An all-in-one Toolkit for Better Machine Translation EvaluationCode1
Language-Informed Beam Search Decoding for Multilingual Machine TranslationCode1
Nested Music Transformer: Sequentially Decoding Compound Tokens in Symbolic Music and Audio GenerationCode1
TasTe: Teaching Large Language Models to Translate through Self-ReflectionCode1
Direct Preference Optimization for Neural Machine Translation with Minimum Bayes Risk DecodingCode1
knn-seq: Efficient, Extensible kNN-MT FrameworkCode1
CLIPTrans: Transferring Visual Knowledge with Pre-trained Models for Multimodal Machine TranslationCode1
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