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

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Showing 6001–6050 of 10752 papers

TitleStatusHype
The Karlsruhe Institute of Technology Systems for the News Translation Task in WMT 2018—0
The JHU Parallel Corpus Filtering Systems for WMT 2018—0
The JHU Machine Translation Systems for WMT 2018—0
The LMU Munich Unsupervised Machine Translation Systems—0
Towards Less Generic Responses in Neural Conversation Models: A Statistical Re-weighting MethodCode0
The MLLP-UPV German-English Machine Translation System for WMT18—0
Tilde's Parallel Corpus Filtering Methods for WMT 2018—0
The IWSLT 2018 Evaluation Campaign—0
The University of Edinburgh's Submissions to the WMT18 News Translation Task—0
The University of Helsinki submissions to the WMT18 news task—0
Turku Neural Parser Pipeline: An End-to-End System for the CoNLL 2018 Shared Task—0
The University of Maryland's Chinese-English Neural Machine Translation Systems at WMT18—0
The Word Sense Disambiguation Test Suite at WMT18—0
The WMT'18 Morpheval test suites for English-Czech, English-German, English-Finnish and Turkish-English—0
Translating a Math Word Problem to a Expression Tree—0
UTFPR at WMT 2018: Minimalistic Supervised Corpora Filtering for Machine Translation—0
The ILSP/ARC submission to the WMT 2018 Parallel Corpus Filtering Shared Task—0
Using Spoken Word Posterior Features in Neural Machine Translation—0
Three Strategies to Improve One-to-Many Multilingual Translation—0
The RWTH Aachen University Supervised Machine Translation Systems for WMT 2018—0
Phrase-Based Attentions—0
Discrete Structural Planning for Generating Diverse Translations—0
Differentiable Expected BLEU for Text Generation—0
Connecting the Dots Between MLE and RL for Sequence Generation—0
AutoLoss: Learning Discrete Schedule for Alternate Optimization—0
Hallucinations in Neural Machine Translation—0
Assumption Questioning: Latent Copying and Reward Exploitation in Question Generation—0
GraphSeq2Seq: Graph-Sequence-to-Sequence for Neural Machine Translation—0
Wronging a Right: Generating Better Errors to Improve Grammatical Error DetectionCode0
Fast and Simple Mixture of Softmaxes with BPE and Hybrid-LightRNN for Language GenerationCode0
Predicting protein secondary structure with Neural Machine Translation—0
Semi-Supervised Sequence Modeling with Cross-View TrainingCode0
Attention-based Encoder-Decoder Networks for Spelling and Grammatical Error Correction—0
NICT's Corpus Filtering Systems for the WMT18 Parallel Corpus Filtering Task—0
NICT's Neural and Statistical Machine Translation Systems for the WMT18 News Translation Task—0
FRAGE: Frequency-Agnostic Word RepresentationCode0
Multi-task Learning with Sample Re-weighting for Machine Reading ComprehensionCode0
Quantum Statistics-Inspired Neural Attention—0
Comparison of Deep Learning and the Classical Machine Learning Algorithm for the Malware Detection—0
Freezing Subnetworks to Analyze Domain Adaptation in Neural Machine Translation—0
XNLI: Evaluating Cross-lingual Sentence RepresentationsCode0
Zero-Shot Cross-lingual Classification Using Multilingual Neural Machine Translation—0
On The Alignment Problem In Multi-Head Attention-Based Neural Machine Translation—0
Greedy Search with Probabilistic N-gram Matching for Neural Machine TranslationCode0
Multilingual Extractive Reading Comprehension by Runtime Machine TranslationCode0
Towards one-shot learning for rare-word translation with external experts—0
Speeding Up Neural Machine Translation Decoding by Cube Pruning—0
An Empirical Investigation into Learning Bug-Fixing Patches in the Wild via Neural Machine Translation—0
Cell-aware Stacked LSTMs for Modeling Sentences—0
Logographic Subword Model for Neural Machine Translation—0
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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
5Transformer (ADMIN init)BLEU score43.8—Unverified
6AdminBLEU 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