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Machine Translation

Machine translation is the task of translating a sentence in a source language to a different target language.

Approaches for machine translation can range from rule-based to statistical to neural-based. More recently, encoder-decoder attention-based architectures like BERT have attained major improvements in machine translation.

One of the most popular datasets used to benchmark machine translation systems is the WMT family of datasets. Some of the most commonly used evaluation metrics for machine translation systems include BLEU, METEOR, NIST, and others.

( Image credit: Google seq2seq )

Papers

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Showing 1951–2000 of 10752 papers

TitleStatusHype
Knowledge-Prompted Estimator: A Novel Approach to Explainable Machine Translation Assessment—0
Measuring Sentiment Bias in Machine Translation—0
Rethinking Translation Memory Augmented Neural Machine Translation—0
Learning Multilingual Sentence Representations with Cross-lingual Consistency RegularizationCode0
A Survey of Vision-Language Pre-training from the Lens of Multimodal Machine Translation—0
Textual Augmentation Techniques Applied to Low Resource Machine Translation: Case of Swahili—0
Neural Machine Translation for the Indigenous Languages of the Americas: An Introduction—0
Modality Influence in Multimodal Machine Learning—0
Adversarial Training For Low-Resource Disfluency CorrectionCode0
Good, but not always Fair: An Evaluation of Gender Bias for three commercial Machine Translation Systems—0
Conformalizing Machine Translation Evaluation—0
Assisting Language Learners: Automated Trans-Lingual Definition Generation via Contrastive Prompt Learning—0
Mixture-of-Supernets: Improving Weight-Sharing Supernet Training with Architecture-Routed Mixture-of-ExpertsCode0
Improving Long Context Document-Level Machine Translation—0
Improving Language Model Integration for Neural Machine Translation—0
On Search Strategies for Document-Level Neural Machine Translation—0
Lenient Evaluation of Japanese Speech Recognition: Modeling Naturally Occurring Spelling Inconsistency—0
PromptRobust: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts—0
Correction of Errors in Preference Ratings from Automated Metrics for Text Generation—0
Prompt Space Optimizing Few-shot Reasoning Success with Large Language ModelsCode0
"A Little is Enough": Few-Shot Quality Estimation based Corpus Filtering improves Machine Translation—0
Extract and Attend: Improving Entity Translation in Neural Machine Translation—0
Text Style Transfer Back-TranslationCode0
Evaluating Machine Translation Quality with Conformal Predictive Distributions—0
Speech Translation with Foundation Models and Optimal Transport: UPC at IWSLT23—0
Assessing the Importance of Frequency versus Compositionality for Subword-based Tokenization in NMTCode0
Improving Polish to English Neural Machine Translation with Transfer Learning: Effects of Data Volume and Language Similarity—0
How Does Pretraining Improve Discourse-Aware Translation?—0
Ethical Considerations for Machine Translation of Indigenous Languages: Giving a Voice to the Speakers—0
Automatic Discrimination of Human and Neural Machine Translation in Multilingual Scenarios—0
Breeding Machine Translations: Evolutionary approach to survive and thrive in the world of automated evaluation—0
The News Delivery Channel Recommendation Based on Granular Neural Network—0
Translation-Enhanced Multilingual Text-to-Image Generation—0
A Corpus for Sentence-level Subjectivity Detection on English News ArticlesCode0
Neural Machine Translation with Dynamic Graph Convolutional Decoder—0
HaVQA: A Dataset for Visual Question Answering and Multimodal Research in Hausa LanguageCode0
Enhancing Translation for Indigenous Languages: Experiments with Multilingual Models—0
Disambiguated Lexically Constrained Neural Machine Translation—0
Parallel Corpus for Indigenous Language Translation: Spanish-Mazatec and Spanish-MixtecCode0
Augmenting Large Language Model Translators via Translation Memories—0
CODET: A Benchmark for Contrastive Dialectal Evaluation of Machine Translation—0
Code-Switched Text Synthesis in Unseen Language Pairs—0
Robustness of Multi-Source MT to Transcription Errors—0
TranSFormer: Slow-Fast Transformer for Machine Translation—0
Gender Lost In Translation: How Bridging The Gap Between Languages Affects Gender Bias in Zero-Shot Multilingual TranslationCode0
Do GPTs Produce Less Literal Translations?Code0
RAMP: Retrieval and Attribute-Marking Enhanced Prompting for Attribute-Controlled Translation—0
On the Copying Problem of Unsupervised NMT: A Training Schedule with a Language Discriminator LossCode0
What about em? How Commercial Machine Translation Fails to Handle (Neo-)Pronouns—0
MTCue: Learning Zero-Shot Control of Extra-Textual Attributes by Leveraging Unstructured Context in Neural Machine TranslationCode0
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All datasetsWMT2014 English-GermanWMT2014 English-FrenchIWSLT2014 German-EnglishACESWMT2016 English-RomanianWMT2016 Romanian-EnglishWMT2014 German-EnglishIWSLT2015 German-EnglishWMT2016 English-GermanIWSLT2015 English-VietnameseIWSLT2015 English-GermanWMT2016 German-English

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Transformer Cycle (Rev)BLEU score35.14—Unverified
2Noisy back-translationBLEU score35—Unverified
3Transformer+Rep(Uni)BLEU score33.89—Unverified
4T5-11BBLEU score32.1—Unverified
5BiBERTBLEU score31.26—Unverified
6Transformer + R-DropBLEU score30.91—Unverified
7Bi-SimCutBLEU score30.78—Unverified
8BERT-fused NMTBLEU score30.75—Unverified
9Data Diversification - TransformerBLEU score30.7—Unverified
10SimCutBLEU score30.56—Unverified
#ModelMetricClaimedVerifiedStatus
1Transformer+BT (ADMIN init)BLEU score46.4—Unverified
2Noisy back-translationBLEU score45.6—Unverified
3mRASP+Fine-TuneBLEU score44.3—Unverified
4Transformer + R-DropBLEU score43.95—Unverified
5AdminBLEU score43.8—Unverified
6Transformer (ADMIN init)BLEU score43.8—Unverified
7BERT-fused NMTBLEU score43.78—Unverified
8MUSE(Paralllel Multi-scale Attention)BLEU score43.5—Unverified
9T5BLEU score43.4—Unverified
10Local Joint Self-attentionBLEU score43.3—Unverified
#ModelMetricClaimedVerifiedStatus
1PiNMTBLEU score40.43—Unverified
2BiBERTBLEU score38.61—Unverified
3Bi-SimCutBLEU score38.37—Unverified
4Cutoff + Relaxed Attention + LMBLEU score37.96—Unverified
5DRDABLEU score37.95—Unverified
6Transformer + R-Drop + CutoffBLEU score37.9—Unverified
7SimCutBLEU score37.81—Unverified
8Cutoff+KneeBLEU score37.78—Unverified
9CutoffBLEU score37.6—Unverified
10CipherDAugBLEU score37.53—Unverified
#ModelMetricClaimedVerifiedStatus
1HWTSC-Teacher-SimScore19.97—Unverified
2MS-COMET-22Score19.89—Unverified
3MS-COMET-QE-22Score19.76—Unverified
4KG-BERTScoreScore17.28—Unverified
5metricx_xl_DA_2019Score17.17—Unverified
6COMET-QEScore16.8—Unverified
7COMET-22Score16.31—Unverified
8UniTE-srcScore15.68—Unverified
9UniTE-refScore15.38—Unverified
10metricx_xxl_DA_2019Score15.24—Unverified