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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 201–250 of 1773 papers

TitleStatusHype
Guiding attention in Sequence-to-sequence models for Dialogue Act predictionCode0
HFT: High Frequency Tokens for Low-Resource NMTCode0
Google's Multilingual Neural Machine Translation System: Enabling Zero-Shot TranslationCode0
Granularity is crucial when applying differential privacy to text: An investigation for neural machine translationCode0
A Copy Mechanism for Handling Knowledge Base Elements in SPARQL Neural Machine TranslationCode0
Greedy Search with Probabilistic N-gram Matching for Neural Machine TranslationCode0
Fully Character-Level Neural Machine Translation without Explicit SegmentationCode0
Gender Inflected or Bias Inflicted: On Using Grammatical Gender Cues for Bias Evaluation in Machine TranslationCode0
Beyond Noise: Mitigating the Impact of Fine-grained Semantic Divergences on Neural Machine TranslationCode0
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine TranslationCode0
From the Paft to the Fiiture: a Fully Automatic NMT and Word Embeddings Method for OCR Post-CorrectionCode0
Guided Alignment Training for Topic-Aware Neural Machine TranslationCode0
Gender Lost In Translation: How Bridging The Gap Between Languages Affects Gender Bias in Zero-Shot Multilingual TranslationCode0
Harnessing Cross-lingual Features to Improve Cognate Detection for Low-resource LanguagesCode0
Beyond BLEU: Training Neural Machine Translation with Semantic SimilarityCode0
F-MALLOC: Feed-forward Memory Allocation for Continual Learning in Neural Machine TranslationCode0
How Grammatical is Character-level Neural Machine Translation? Assessing MT Quality with Contrastive Translation PairsCode0
An Empirical Study of Consistency Regularization for End-to-End Speech-to-Text TranslationCode0
An Evaluation of Neural Machine Translation Models on Historical Spelling NormalizationCode0
Improved Neural Machine Translation with a Syntax-Aware Encoder and DecoderCode0
Better Neural Machine Translation by Extracting Linguistic Information from BERTCode0
Improving End-to-End Speech Translation by Imitation-Based Knowledge Distillation with Synthetic TranscriptsCode0
First the worst: Finding better gender translations during beam searchCode0
From Priest to Doctor: Domain Adaptaion for Low-Resource Neural Machine TranslationCode0
Improving Neural Machine Translation with the Abstract Meaning Representation by Combining Graph and Sequence TransformersCode0
BPE beyond Word Boundary: How NOT to use Multi Word Expressions in Neural Machine TranslationCode0
Generalised Unsupervised Domain Adaptation of Neural Machine Translation with Cross-Lingual Data SelectionCode0
Finding Better Subword Segmentation for Neural Machine TranslationCode0
Finding Memo: Extractive Memorization in Constrained Sequence Generation TasksCode0
Incorporating Discrete Translation Lexicons into Neural Machine TranslationCode0
Addressing the Vulnerability of NMT in Input PerturbationsCode0
FGraDA: A Dataset and Benchmark for Fine-Grained Domain Adaptation in Machine TranslationCode0
Fine-grained Human Evaluation of Transformer and Recurrent Approaches to Neural Machine Translation for English-to-ChineseCode0
Exploring Unsupervised Pretraining Objectives for Machine TranslationCode0
Addressing the Rare Word Problem in Neural Machine TranslationCode0
Faithful Target Attribute Prediction in Neural Machine TranslationCode0
Exploring Paracrawl for Document-level Neural Machine TranslationCode0
Byte-based Multilingual NMT for Endangered LanguagesCode0
Exploring Recombination for Efficient Decoding of Neural Machine TranslationCode0
Fine-Tuning MT systems for Robustness to Second-Language Speaker VariationsCode0
Generating Authentic Adversarial Examples beyond Meaning-preserving with Doubly Round-trip TranslationCode0
Improving Neural Machine Translation Robustness via Data Augmentation: Beyond Back-TranslationCode0
Enhancing Neural Machine Translation with Semantic UnitsCode0
An Effective Method using Phrase Mechanism in Neural Machine TranslationCode0
Ensembling Factored Neural Machine Translation Models for Automatic Post-Editing and Quality EstimationCode0
Learning Multilingual Sentence Representations with Cross-lingual Consistency RegularizationCode0
A Classification-Guided Approach for Adversarial Attacks against Neural Machine TranslationCode0
Learning to Remember Translation History with a Continuous CacheCode0
CantonMT: Cantonese to English NMT Platform with Fine-Tuned Models Using Synthetic Back-Translation DataCode0
Examining the Tip of the Iceberg: A Data Set for Idiom TranslationCode0
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