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 92269250 of 10752 papers

TitleStatusHype
Fast and Robust Neural Network Joint Models for Statistical Machine Translation0
Domain Adaptation for Medical Text Translation using Web Resources0
A Unified Framework for Grammar Error Correction0
Crowdsourcing High-Quality Parallel Data Extraction from Twitter0
Hippocratic Abbreviation Expansion0
Learning New Semi-Supervised Deep Auto-encoder Features for Statistical Machine Translation0
Adaptive Quality Estimation for Machine Translation0
Augmenting String-to-Tree and Tree-to-String Translation with Non-Syntactic Phrases0
New Directions in Vector Space Models of Meaning0
Faster Phrase-Based Decoding by Refining Feature State0
Machine Translation of Medical Texts in the Khresmoi Project0
Learning Polylingual Topic Models from Code-Switched Social Media Documents0
DCU-Lingo24 Participation in WMT 2014 Hindi-English Translation task0
Linear Mixture Models for Robust Machine Translation0
A Hybrid Approach to Skeleton-based Translation0
POSTECH Grammatical Error Correction System in the CoNLL-2014 Shared Task0
Proceedings of the Ninth Workshop on Statistical Machine Translation0
Postech's System Description for Medical Text Translation Task0
Low-Resource Semantic Role Labeling0
Constructing a Turkish-English Parallel TreeBank0
Experiments in Medical Translation Shared Task at WMT 20140
FBK-UPV-UEdin participation in the WMT14 Quality Estimation shared-task0
Hierarchical MT Training using Max-Violation Perceptron0
Results of the WMT14 Metrics Shared Task0
A Constrained Viterbi Relaxation for Bidirectional Word Alignment0
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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
5AdminBLEU score43.8Unverified
6Transformer (ADMIN init)BLEU 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