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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 1601–1650 of 1773 papers

TitleStatusHype
Dual Past and Future for Neural Machine Translation—0
Controllable Dual Skew Divergence Loss for Neural Machine Translation—0
Dynamic Adaptation of Neural Machine-Translation Systems Through Translation Exemplars—0
Dynamic Curriculum Learning for Low-Resource Neural Machine Translation—0
Dynamic Fusion: Attentional Language Model for Neural Machine Translation—0
Dynamic Oracle for Neural Machine Translation in Decoding Phase—0
Dynamic Position Encoding for Transformers—0
Dynamic Sentence Sampling for Efficient Training of Neural Machine Translation—0
Echo State Neural Machine Translation—0
Echo: Compiler-based GPU Memory Footprint Reduction for LSTM RNN Training—0
EdinSaar@WMT21: North-Germanic Low-Resource Multilingual NMT—0
EduMT: Developing Machine Translation System for Educational Content in Indian Languages—0
Effectively pretraining a speech translation decoder with Machine Translation data—0
Effective Parallel Corpus Mining using Bilingual Sentence Embeddings—0
Effective Use of Target-side Context for Neural Machine Translation—0
Efficient Bilingual Generalization from Neural Transduction Grammar Induction—0
Efficient Inference for Multilingual Neural Machine Translation—0
Efficient Neural Machine Translation for Low-Resource Languages via Exploiting Related Languages—0
Efficient Neural Machine Translation with Prior Word Alignment—0
Efficient Technical Term Translation: A Knowledge Distillation Approach for Parenthetical Terminology Translation—0
Efficient Transfer Learning for Quality Estimation with Bottleneck Adapter Layer—0
Efficient Unsupervised NMT for Related Languages with Cross-Lingual Language Models and Fidelity Objectives—0
Effort-Aware Neural Automatic Post-Editing—0
Efforts Towards Developing a Tamang Nepali Machine Translation System—0
EMMeTT: Efficient Multimodal Machine Translation Training—0
Empirical Analysis of Korean Public AI Hub Parallel Corpora and in-depth Analysis using LIWC—0
Empirical Evaluation of Active Learning Techniques for Neural MT—0
Enabling Multi-Source Neural Machine Translation By Concatenating Source Sentences In Multiple Languages—0
Encoders Help You Disambiguate Word Senses in Neural Machine Translation—0
Encoding Gated Translation Memory into Neural Machine Translation—0
Encodings of Source Syntax: Similarities in NMT Representations Across Target Languages—0
ENCORE: Ensemble Learning using Convolution Neural Machine Translation for Automatic Program Repair—0
Encouraging Lexical Translation Consistency for Document-Level Neural Machine Translation—0
End to end Hindi to English speech conversion using Bark, mBART and a finetuned XLSR Wav2Vec2—0
End-to-End Simultaneous Speech Translation with Pretraining and Distillation: Huawei Noah’s System for AutoSimTranS 2022—0
English-Czech Systems in WMT19: Document-Level Transformer—0
English-Indonesian Neural Machine Translation for Spoken Language Domains—0
English-Myanmar NMT and SMT with Pre-ordering: NICT’s Machine Translation Systems at WAT-2018—0
English-Myanmar Supervised and Unsupervised NMT: NICT's Machine Translation Systems at WAT-2019—0
English-Russian Data Augmentation for Neural Machine Translation—0
English to Bengali Multimodal Neural Machine Translation using Transliteration-based Phrase Pairs Augmentation—0
English-to-Chinese Transliteration with Phonetic Auxiliary Task—0
English to Hindi Multi-modal Neural Machine Translation and Hindi Image Captioning—0
English-to-Japanese Diverse Translation by Combining Forward and Backward Outputs—0
Enhancing Entertainment Translation for Indian Languages using Adaptive Context, Style and LLMs—0
Enhancing Language Learning through Technology: Introducing a New English-Azerbaijani (Arabic Script) Parallel Corpus—0
Enhancing Meme Token Market Transparency: A Multi-Dimensional Entity-Linked Address Analysis for Liquidity Risk Evaluation—0
Enhancing Supervised Learning with Contrastive Markings in Neural Machine Translation Training—0
Enhancing the Nonlinear Mutual Dependencies in Transformers with Mutual Information—0
Ensemble Distillation for Neural Machine Translation—0
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