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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 1451–1500 of 1773 papers

TitleStatusHype
On the Copying Behaviors of Pre-Training for Neural Machine TranslationCode0
On the Copying Problem of Unsupervised NMT: A Training Schedule with a Language Discriminator LossCode0
Faithful Target Attribute Prediction in Neural Machine TranslationCode0
F-MALLOC: Feed-forward Memory Allocation for Continual Learning in Neural Machine TranslationCode0
Doubly-Trained Adversarial Data Augmentation for Neural Machine TranslationCode0
CantonMT: Cantonese to English NMT Platform with Fine-Tuned Models Using Synthetic Back-Translation DataCode0
On the Difficulty of Translating Free-Order Case-Marking LanguagesCode0
Calibrating Translation Decoding with Quality Estimation on LLMsCode0
Zero-shot Cross-lingual Transfer of Neural Machine Translation with Multilingual Pretrained EncodersCode0
Are Character-level Translations Worth the Wait? Comparing ByT5 and mT5 for Machine TranslationCode0
From Priest to Doctor: Domain Adaptaion for Low-Resource Neural Machine TranslationCode0
From the Paft to the Fiiture: a Fully Automatic NMT and Word Embeddings Method for OCR Post-CorrectionCode0
Fully Character-Level Neural Machine Translation without Explicit SegmentationCode0
A Token-level Contrastive Framework for Sign Language TranslationCode0
Consistency by Agreement in Zero-shot Neural Machine TranslationCode0
Don't Overlook the Grammatical Gender: Bias Evaluation for Hindi-English Machine TranslationCode0
Modeling Baroque Two-Part Counterpoint with Neural Machine TranslationCode0
Do Not Change Me: On Transferring Entities Without Modification in Neural Machine Translation -- a Multilingual PerspectiveCode0
Gender Inflected or Bias Inflicted: On Using Grammatical Gender Cues for Bias Evaluation in Machine TranslationCode0
Gender Lost In Translation: How Bridging The Gap Between Languages Affects Gender Bias in Zero-Shot Multilingual TranslationCode0
Transfer Learning for Low-Resource Neural Machine TranslationCode0
On the Importance of Word Boundaries in Character-level Neural Machine TranslationCode0
Generalised Unsupervised Domain Adaptation of Neural Machine Translation with Cross-Lingual Data SelectionCode0
Modeling Coverage for Neural Machine TranslationCode0
Compression of Neural Machine Translation Models via PruningCode0
A Document-Level Neural Machine Translation Model with Dynamic Caching Guided by Theme-Rheme InformationCode0
Generating Authentic Adversarial Examples beyond Meaning-preserving with Doubly Round-trip TranslationCode0
TransFool: An Adversarial Attack against Neural Machine Translation ModelsCode0
A Comparative Study of LLMs, NMT Models, and Their Combination in Persian-English Idiom TranslationCode0
Exploring Unsupervised Pretraining Objectives for Machine TranslationCode0
Token Drop mechanism for Neural Machine TranslationCode0
Exploring Recombination for Efficient Decoding of 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
Granularity is crucial when applying differential privacy to text: An investigation for neural machine translationCode0
Rule-based Morphological Inflection Improves Neural Terminology TranslationCode0
Modeling Past and Future for Neural Machine TranslationCode0
Greedy Search with Probabilistic N-gram Matching for Neural Machine TranslationCode0
Guided Alignment Training for Topic-Aware Neural Machine TranslationCode0
Saliency-driven Word Alignment Interpretation for Neural Machine TranslationCode0
Guiding attention in Sequence-to-sequence models for Dialogue Act predictionCode0
Incorporating Chinese Radicals Into Neural Machine Translation: Deeper Than Character LevelCode0
Salute the Classic: Revisiting Challenges of Machine Translation in the Age of Large Language ModelsCode0
Byte-based Multilingual NMT for Endangered LanguagesCode0
Domain Robustness in Neural Machine TranslationCode0
Handling Syntactic Divergence in Low-resource Machine TranslationCode0
Bridging the Gap between Training and Inference: Multi-Candidate Optimization for Diverse Neural Machine TranslationCode0
Harnessing Cross-lingual Features to Improve Cognate Detection for Low-resource LanguagesCode0
On Using Distribution-Based Compositionality Assessment to Evaluate Compositional Generalisation in Machine TranslationCode0
Exploring Paracrawl for Document-level Neural Machine TranslationCode0
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