SOTAVerified

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

Showing 39013950 of 10752 papers

TitleStatusHype
Filtering Back-Translated Data in Unsupervised Neural Machine Translation0
Corpus and dictionary development for classifiers/quantifiers towards a French-Japanese machine translation0
A tree is a Baum is an \'arbol is a sach'a: Creating a trilingual treebank0
A Multi-media Approach to Cross-lingual Entity Knowledge Transfer0
Filtering Pseudo-References by Paraphrasing for Automatic Evaluation of Machine Translation0
Finding Alternative Translations in a Large Corpus of Movie Subtitle0
Corpora Generation for Grammatical Error Correction0
Finding Challenging Metaphors that Confuse Pretrained Language Models0
Finding Good Enough: A Task-Based Evaluation of Query Biased Summarization for Cross-Language Information Retrieval0
Are we Estimating or Guesstimating Translation Quality?0
Finding More Bilingual Webpages with High Credibility via Link Analysis0
Finding Optimal 1-Endpoint-Crossing Trees0
Finding Replicable Human Evaluations via Stable Ranking Probability0
Findings of the 2012 Workshop on Statistical Machine Translation0
Findings of the 2013 Workshop on Statistical Machine Translation0
Findings of the 2014 Workshop on Statistical Machine Translation0
Findings of the 2015 Workshop on Statistical Machine Translation0
Findings of the 2016 Conference on Machine Translation0
Corpora for Document-Level Neural Machine Translation0
Addressing Posterior Collapse with Mutual Information for Improved Variational Neural Machine Translation0
Findings of the 2018 Conference on Machine Translation (WMT18)0
Findings of the 2019 Conference on Machine Translation (WMT19)0
Findings of the 2020 Conference on Machine Translation (WMT20)0
Findings of the 2021 Conference on Machine Translation (WMT21)0
Findings of the AmericasNLP 2021 Shared Task on Open Machine Translation for Indigenous Languages of the Americas0
Findings of the Covid-19 MLIA Machine Translation Task0
Findings of the First Shared Task on Lifelong Learning Machine Translation0
CNGL-CORE: Referential Translation Machines for Measuring Semantic Similarity0
Findings of the Fourth Workshop on Neural Generation and Translation0
Findings of the LoResMT 2020 Shared Task on Zero-Shot for Low-Resource languages0
Findings of the LoResMT 2021 Shared Task on COVID and Sign Language for Low-resource Languages0
Findings of the Second Shared Task on Multimodal Machine Translation and Multilingual Image Description0
Findings of the Second Workshop on Automatic Simultaneous Translation0
Findings of the Second Workshop on Neural Machine Translation and Generation0
Corpora for Cross-Language Information Retrieval in Six Less-Resourced Languages0
Co-regularizing character-based and word-based models for semi-supervised Chinese word segmentation0
CoAM: Corpus of All-Type Multiword Expressions0
Findings of the WMT 2016 Bilingual Document Alignment Shared Task0
Findings of the WMT 2017 Biomedical Translation Shared Task0
Findings of the WMT 2018 Biomedical Translation Shared Task: Evaluation on Medline test sets0
Findings of the WMT 2018 Shared Task on Automatic Post-Editing0
Findings of the WMT 2018 Shared Task on Quality Estimation0
A Multilingual Wikified Data Set of Educational Material0
Findings of the WMT 2019 Shared Task on Automatic Post-Editing0
Findings of the WMT 2019 Shared Task on Parallel Corpus Filtering for Low-Resource Conditions0
Findings of the WMT 2019 Shared Tasks on Quality Estimation0
A Comparative Study of Post-editing Guidelines0
Forest Reranking through Subtree Ranking0
Co-Regression for Cross-Language Review Rating Prediction0
Coreference Strategies in English-German Translation0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Transformer Cycle (Rev)BLEU score35.14Unverified
2Noisy back-translationBLEU score35Unverified
3Transformer+Rep(Uni)BLEU score33.89Unverified
4T5-11BBLEU score32.1Unverified
5BiBERTBLEU score31.26Unverified
6Transformer + R-DropBLEU score30.91Unverified
7Bi-SimCutBLEU score30.78Unverified
8BERT-fused NMTBLEU score30.75Unverified
9Data Diversification - TransformerBLEU score30.7Unverified
10SimCutBLEU score30.56Unverified
#ModelMetricClaimedVerifiedStatus
1Transformer+BT (ADMIN init)BLEU score46.4Unverified
2Noisy back-translationBLEU score45.6Unverified
3mRASP+Fine-TuneBLEU score44.3Unverified
4Transformer + R-DropBLEU score43.95Unverified
5Transformer (ADMIN init)BLEU score43.8Unverified
6AdminBLEU score43.8Unverified
7BERT-fused NMTBLEU score43.78Unverified
8MUSE(Paralllel Multi-scale Attention)BLEU score43.5Unverified
9T5BLEU score43.4Unverified
10Local Joint Self-attentionBLEU score43.3Unverified
#ModelMetricClaimedVerifiedStatus
1PiNMTBLEU score40.43Unverified
2BiBERTBLEU score38.61Unverified
3Bi-SimCutBLEU score38.37Unverified
4Cutoff + Relaxed Attention + LMBLEU score37.96Unverified
5DRDABLEU score37.95Unverified
6Transformer + R-Drop + CutoffBLEU score37.9Unverified
7SimCutBLEU score37.81Unverified
8Cutoff+KneeBLEU score37.78Unverified
9CutoffBLEU score37.6Unverified
10CipherDAugBLEU score37.53Unverified
#ModelMetricClaimedVerifiedStatus
1HWTSC-Teacher-SimScore19.97Unverified
2MS-COMET-22Score19.89Unverified
3MS-COMET-QE-22Score19.76Unverified
4KG-BERTScoreScore17.28Unverified
5metricx_xl_DA_2019Score17.17Unverified
6COMET-QEScore16.8Unverified
7COMET-22Score16.31Unverified
8UniTE-srcScore15.68Unverified
9UniTE-refScore15.38Unverified
10metricx_xxl_DA_2019Score15.24Unverified