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 5151–5200 of 10752 papers

TitleStatusHype
Towards Better Modeling Hierarchical Structure for Self-Attention with Ordered Neurons—0
The Bottom-up Evolution of Representations in the Transformer: A Study with Machine Translation and Language Modeling Objectives—0
Multi-agent Learning for Neural Machine Translation—0
Hybrid Data-Model Parallel Training for Sequence-to-Sequence Recurrent Neural Network Machine Translation—0
Improving Context-aware Neural Machine Translation with Target-side Context—0
Bilingual Low-Resource Neural Machine Translation with Round-Tripping: The Case of Persian-Spanish—0
Statistical Machine Translation between Myanmar (Burmese) and Dawei (Tavoyan)—0
Taking MT Evaluation Metrics to Extremes: Beyond Correlation with Human Judgments—0
Are ambiguous conjunctions problematic for machine translation?—0
Dependency-Based Relative Positional Encoding for Transformer NMT—0
Dependency-Based Self-Attention for Transformer NMT—0
Designing a Frame-Semantic Machine Translation Evaluation Metric—0
A Unified Neural Coherence Model—0
Enhancing Phrase-Based Statistical Machine Translation by Learning Phrase Representations Using Long Short-Term Memory Network—0
Combining PBSMT and NMT Back-translated Data for Efficient NMT—0
Optimising the Machine Translation Post-editing Workflow—0
Automated Text Simplification as a Preprocessing Step for Machine Translation into an Under-resourced Language—0
Exploring Adequacy Errors in Neural Machine Translation with the Help of Cross-Language Aligned Word Embeddings—0
Study on Unsupervised Statistical Machine Translation for Backtranslation—0
Comparing a Hand-crafted to an Automatically Generated Feature Set for Deep Learning: Pairwise Translation Evaluation—0
Investigating Terminology Translation in Statistical and Neural Machine Translation: A Case Study on English-to-Hindi and Hindi-to-English—0
Comparing MT Approaches for Text Normalization—0
Evaluating the Cross-Lingual Effectiveness of Massively Multilingual Neural Machine Translation—0
Automatic Detection of Translation Direction—0
Comparison between NMT and PBSMT Performance for Translating Noisy User-Generated Content—0
Corpus Linguistics, Translation and Error Analysis—0
One Model to Learn Both: Zero Pronoun Prediction and Translation—0
Adding Linguistic Knowledge to NLP Tasks for Bulgarian: The Verb Paradigm Patterns—0
Naive Regularizers for Low-Resource Neural Machine Translation—0
A Discriminative Neural Model for Cross-Lingual Word Alignment—0
Automatic Propbank Generation for Turkish—0
Human Evaluation of Neural Machine Translation: The Case of Deep Learning—0
The Punster's Amanuensis: The Proper Place of Humans and Machines in the Translation of Wordplay—0
Towards Understanding Neural Machine Translation with Word Importance—0
The Four Stages of Machine Translation Acceptance in a Freelancer's Life—0
The OPUS Resource Repository: An Open Package for Creating Parallel Corpora and Machine Translation Services—0
Scale Calibrated Training: Improving Generalization of Deep Networks via Scale-Specific Normalization—0
Generating Classical Chinese Poems from Vernacular ChineseCode0
Improving Multi-Head Attention with Capsule Networks—0
Entity Projection via Machine Translation for Cross-Lingual NERCode0
Evaluating Pronominal Anaphora in Machine Translation: An Evaluation Measure and a Test SuiteCode0
Explicit Cross-lingual Pre-training for Unsupervised Machine Translation—0
NCLS: Neural Cross-Lingual SummarizationCode0
Improving Back-Translation with Uncertainty-based Confidence EstimationCode0
Latent Part-of-Speech Sequences for Neural Machine Translation—0
Handling Syntactic Divergence in Low-resource Machine TranslationCode0
Encoders Help You Disambiguate Word Senses in Neural Machine Translation—0
Bilingual is At Least Monolingual (BALM): A Novel Translation Algorithm that Encodes Monolingual PriorsCode0
Transformer Dissection: A Unified Understanding of Transformer's Attention via the Lens of KernelCode0
Regularized Context Gates on Transformer for 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