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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
Greedy Search with Probabilistic N-gram Matching for Neural Machine TranslationCode0
Generating Gender Augmented Data for NLPCode0
Bi-Directional Differentiable Input Reconstruction for Low-Resource Neural Machine TranslationCode0
A Copy Mechanism for Handling Knowledge Base Elements in SPARQL Neural Machine TranslationCode0
Gender Lost In Translation: How Bridging The Gap Between Languages Affects Gender Bias in Zero-Shot Multilingual TranslationCode0
Guided Alignment Training for Topic-Aware Neural Machine TranslationCode0
Impact of Visual Context on Noisy Multimodal NMT: An Empirical Study for English to Indian LanguagesCode0
F-MALLOC: Feed-forward Memory Allocation for Continual Learning in Neural Machine TranslationCode0
Generalised Unsupervised Domain Adaptation of Neural Machine Translation with Cross-Lingual Data SelectionCode0
Generating Authentic Adversarial Examples beyond Meaning-preserving with Doubly Round-trip TranslationCode0
From Priest to Doctor: Domain Adaptaion for Low-Resource Neural Machine TranslationCode0
Beyond Noise: Mitigating the Impact of Fine-grained Semantic Divergences on Neural Machine TranslationCode0
Google's Multilingual Neural Machine Translation System: Enabling Zero-Shot 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
Fine-grained Human Evaluation of Transformer and Recurrent Approaches to Neural Machine Translation for English-to-ChineseCode0
Handling Syntactic Divergence in Low-resource Machine TranslationCode0
Bitext Mining Using Distilled Sentence Representations for Low-Resource LanguagesCode0
Beyond BLEU: Training Neural Machine Translation with Semantic SimilarityCode0
Fine-Tuning MT systems for Robustness to Second-Language Speaker VariationsCode0
How do lexical semantics affect translation? An empirical studyCode0
How Grammatical is Character-level Neural Machine Translation? Assessing MT Quality with Contrastive Translation PairsCode0
Achieving Open Vocabulary Neural Machine Translation with Hybrid Word-Character ModelsCode0
Improving Back-Translation with Uncertainty-based Confidence EstimationCode0
An Empirical Study of Consistency Regularization for End-to-End Speech-to-Text TranslationCode0
BPE beyond Word Boundary: How NOT to use Multi Word Expressions in Neural Machine TranslationCode0
Better Neural Machine Translation by Extracting Linguistic Information from BERTCode0
Finding Memo: Extractive Memorization in Constrained Sequence Generation TasksCode0
First the worst: Finding better gender translations during beam searchCode0
Improving Neural Machine Translation Robustness via Data Augmentation: Beyond Back-TranslationCode0
Fully Character-Level Neural Machine Translation without Explicit SegmentationCode0
Faithful Target Attribute Prediction in Neural Machine TranslationCode0
FGraDA: A Dataset and Benchmark for Fine-Grained Domain Adaptation in Machine TranslationCode0
Addressing the Vulnerability of NMT in Input PerturbationsCode0
Factored Neural Machine TranslationCode0
Exploring Paracrawl for Document-level Neural Machine TranslationCode0
Instance Weighting for Neural Machine Translation Domain AdaptationCode0
Byte-based Multilingual NMT for Endangered LanguagesCode0
Addressing the Rare Word Problem in Neural Machine TranslationCode0
Exploring Recombination for Efficient Decoding of Neural Machine TranslationCode0
Exploiting Out-of-Domain Parallel Data through Multilingual Transfer Learning for Low-Resource Neural Machine TranslationCode0
Exploiting Social Media Content for Self-Supervised Style TransferCode0
Exploring Unsupervised Pretraining Objectives for Machine TranslationCode0
Finding Better Subword Segmentation for Neural Machine TranslationCode0
Joint Dropout: Improving Generalizability in Low-Resource Neural Machine Translation through Phrase Pair VariablesCode0
Gender Inflected or Bias Inflicted: On Using Grammatical Gender Cues for Bias Evaluation in Machine TranslationCode0
Improved Neural Machine Translation with a Syntax-Aware Encoder and DecoderCode0
Learning to translate by learning to communicateCode0
Enhancing Neural Machine Translation with Semantic UnitsCode0
Ensembling Factored Neural Machine Translation Models for Automatic Post-Editing and Quality EstimationCode0
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