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 78017850 of 10752 papers

TitleStatusHype
Letter Sequence Labeling for Compound Splitting0
Proceedings of the First Conference on Machine Translation: Volume 2, Shared Task Papers0
ILLC-UvA Adaptation System (Scorpio) at WMT'16 IT-DOMAIN Task0
Synthesizing Compound Words for Machine Translation0
Metrics for Evaluation of Word-level Machine Translation Quality Estimation0
Target-Bidirectional Neural Models for Machine Transliteration0
Fast and highly parallelizable phrase table for statistical machine translation0
MUTT: Metric Unit TesTing for Language Generation Tasks0
DOCAL - Vicomtech's Participation in the WMT16 Shared Task on Bilingual Document Alignment0
Results of the WMT16 Metrics Shared Task0
SHEF-Multimodal: Grounding Machine Translation on Images0
DocChat: An Information Retrieval Approach for Chatbot Engines Using Unstructured Documents0
SHEF-MIME: Word-level Quality Estimation Using Imitation Learning0
Evaluating and Combining Name Entity Recognition Systems0
First Steps Towards Coverage-Based Document Alignment0
LIMSI's Contribution to the WMT'16 Biomedical Translation Task0
Leveraging Entity Linking and Related Language Projection to Improve Name Transliteration0
Incorporating Relational Knowledge into Word Representations using Subspace Regularization0
Embeddings for Word Sense Disambiguation: An Evaluation StudyCode0
Bilingual Embeddings and Word Alignments for Translation Quality Estimation0
JU-USAAR: A Domain Adaptive MT System0
Learning Structured Predictors from Bandit Feedback for Interactive NLP0
Different Flavors of GUM: Evaluating Genre and Sentence Type Effects on Multilayer Corpus Annotation Quality0
Inner Attention based Recurrent Neural Networks for Answer Selection0
Referential Translation Machines for Predicting Translation Performance0
SHEF-LIUM-NN: Sentence level Quality Estimation with Neural Network Features0
Dictionary-based Domain Adaptation of MT Systems without Retraining0
A Continuous Space Rule Selection Model for Syntax-based Statistical Machine Translation0
A Corpus of Preposition Supersenses0
Improving Statistical Machine Translation Performance by Oracle-BLEU Model Re-estimation0
SoNLP-DP System for ConLL-2016 English Shallow Discourse Parsing0
The Edinburgh/LMU Hierarchical Machine Translation System for WMT 20160
Edinburgh's Statistical Machine Translation Systems for WMT160
CharacTer: Translation Edit Rate on Character Level0
Predicting the Compositionality of Nominal Compounds: Giving Word Embeddings a Hard Time0
It-disambiguation and source-aware language models for cross-lingual pronoun prediction0
DFKI's system for WMT16 IT-domain task, including analysis of systematic errors0
Computational Natural Language Learning: +-20years +-Data +-Features +-Multimodal +-Bioplausible0
A Linear Baseline Classifier for Cross-Lingual Pronoun Prediction0
Sheffield Systems for the English-Romanian WMT Translation Task0
Graph-Based Translation Via Graph Segmentation0
MED: The LMU System for the SIGMORPHON 2016 Shared Task on Morphological Reinflection0
Domain Specific Named Entity Recognition Referring to the Real World by Deep Neural Networks0
LIMSI@WMT'16: Machine Translation of News0
A Domain Adaptation Regularization for Denoising Autoencoders0
Learning Paraphrasing for Multiword Expressions0
Graph-based Dependency Parsing with Bidirectional LSTM0
Pronoun Prediction with Linguistic Features and Example Weighing0
Pronoun Prediction with Latent Anaphora Resolution0
Jointly Learning to Embed and Predict with Multiple Languages0
Show:102550
← PrevPage 157 of 216Next →

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