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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 3101–3150 of 10752 papers

TitleStatusHype
Zero-Shot Translation using Diffusion Models—0
Translating Headers of Tabular Data: A Pilot Study of Schema Translation—0
MiSS: An Assistant for Multi-Style Simultaneous Translation—0
NoahNMT at WMT 2021: Dual Transfer for Very Low Resource Supervised Machine Translation—0
SpanAlign: Efficient Sequence Tagging Annotation Projection into Translated Data applied to Cross-Lingual Opinion Mining—0
Sequence-to-Lattice Models for Fast Translation—0
On the Stability of System Rankings at WMTCode0
Adapting Neural Machine Translation for Automatic Post-Editing—0
Adapting Entities across Languages and Cultures—0
ISTIC’s Triangular Machine Translation System for WMT2021—0
Machine Translation for Zero and Low-resourced Dialects using a New Extended Version of the Dialectal Parallel Corpus (Padic v2.0)—0
Improving the Quality Trade-Off for Neural Machine Translation Multi-Domain Adaptation—0
The TALP-UPC Participation in WMT21 News Translation Task: an mBART-based NMT Approach—0
Agree to Disagree: Analysis of Inter-Annotator Disagreements in Human Evaluation of Machine Translation Output—0
Transfer Learning with Shallow Decoders: BSC at WMT2021’s Multilingual Low-Resource Translation for Indo-European Languages Shared TaskCode0
Error Identification for Machine Translation with Metric Embedding and Attention—0
A3-108 Machine Translation System for Similar Language Translation Shared Task 2021—0
Mutual-Learning Improves End-to-End Speech Translation—0
MiSS@WMT21: Contrastive Learning-reinforced Domain Adaptation in Neural Machine Translation—0
A Generative Framework for Simultaneous Machine Translation—0
Japanese Zero Anaphora Resolution Can Benefit from Parallel Texts Through Neural Transfer Learning—0
DUTNLP Machine Translation System for WMT21 Triangular Translation Task—0
Tencent AI Lab Machine Translation Systems for the WMT21 Biomedical Translation Task—0
Pruning Neural Machine Translation for Speed Using Group Lasso—0
Don’t Go Far Off: An Empirical Study on Neural Poetry Translation—0
TermMind: Alibaba’s WMT21 Machine Translation Using Terminologies Task Submission—0
Multilingual Machine Translation Evaluation Metrics Fine-tuned on Pseudo-Negative Examples for WMT 2021 Metrics Task—0
NRC-CNRC Systems for Upper Sorbian-German and Lower Sorbian-German Machine Translation 2021—0
Two Heads are Better than One? Verification of Ensemble Effect in Neural Machine Translation—0
Set Generation Networks for End-to-End Knowledge Base Population—0
Investigating the Helpfulness of Word-Level Quality Estimation for Post-Editing Machine Translation OutputCode0
Beyond Grammatical Error Correction: Improving L1-influenced research writing in English using pre-trained encoder-decoder modelsCode0
Findings of the WMT Shared Task on Machine Translation Using Terminologies—0
A Fine-Grained Analysis of BERTScore—0
Similar Language Translation for Catalan, Portuguese and Spanish Using Marian NMT—0
Self-Supervised Quality Estimation for Machine Translation—0
Direct Exploitation of Attention Weights for Translation Quality Estimation—0
Lingua Custodia’s Participation at the WMT 2021 Machine Translation Using Terminologies Shared Task—0
GFST: Gender-Filtered Self-Training for More Accurate Gender in TranslationCode0
To Optimize, or Not to Optimize, That Is the Question: TelU-KU Models for WMT21 Large-Scale Multilingual Machine Translation—0
Bandits Don’t Follow Rules: Balancing Multi-Facet Machine Translation with Multi-Armed Bandits—0
Fix-Filter-Fix: Intuitively Connect Any Models for Effective Bug Fixing—0
Backtranslation in Neural Morphological Inflection—0
Findings of the WMT 2021 Shared Task on Quality Estimation—0
Findings of the WMT 2021 Shared Task on Large-Scale Multilingual Machine Translation—0
An Empirical Investigation of Word Alignment Supervision for Zero-Shot Multilingual Neural Machine Translation—0
FJWU Participation for the WMT21 Biomedical Translation Task—0
DELA Corpus - A Document-Level Corpus Annotated with Context-Related IssuesCode0
The LMU Munich System for the WMT 2021 Large-Scale Multilingual Machine Translation Shared Task—0
Entity-level Cross-modal Learning Improves Multi-modal 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
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