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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 4801–4850 of 10752 papers

TitleStatusHype
Predicting Machine Translation Adequacy with Document Embeddings—0
Predicting Machine Translation Performance on Low-Resource Languages: The Role of Domain Similarity—0
MTUncertainty: Assessing the Need for Post-editing of Machine Translation Outputs by Fine-tuning OpenAI LLMs—0
Predicting Prepositions for SMT—0
Predicting Pronouns across Languages with Continuous Word Spaces—0
Predicting Pronouns with a Convolutional Network and an N-gram Model—0
Predicting Pronoun Translation Using Syntactic, Morphological and Contextual Features from Parallel Data—0
Predicting protein secondary structure with Neural Machine Translation—0
Predicting Target Language CCG Supertags Improves Neural Machine Translation—0
Predicting the Compositionality of Multiword Expressions Using Translations in Multiple Languages—0
Predicting the Compositionality of Nominal Compounds: Giving Word Embeddings a Hard Time—0
Predicting the impact of dataset composition on model performance—0
Predicting the Mumble of Wireless Channel with Sequence-to-Sequence Models—0
Predicting the Ordering of Characters in Japanese Historical Documents—0
Predicting Translation Equivalents in Linked WordNets—0
Predicting Translation Performance with Referential Translation Machines—0
Predicting Word Similarity in Context with Referential Translation Machines—0
Prediction Difference Regularization against Perturbation for Neural Machine Translation—0
Prediction Improves Simultaneous Neural Machine Translation—0
Prediction of Learning Curves in Machine Translation—0
Prediction of Translation Techniques for the Translation Process—0
Predictive Attention Transformer: Improving Transformer with Attention Map Prediction—0
Predictor-Corrector Enhanced Transformers with Exponential Moving Average Coefficient Learning—0
Predictor-Estimator using Multilevel Task Learning with Stack Propagation for Neural Quality Estimation—0
Pre-editing Plus Neural Machine Translation for Subtitling: Effective Pre-editing Rules for Subtitling of TED Talks—0
Preference Grammars and Soft Syntactic Constraints for GHKM Syntax-based Statistical Machine Translation—0
PREFER: Using a Graph-Based Approach to Generate Paraphrases for Language Learning—0
Prefix Embeddings for In-context Machine Translation—0
Prefix Lexicalization of Synchronous CFGs using Synchronous TAG—0
Prefix Text as a Yarn: Eliciting Non-English Alignment in Foundation Language Model—0
Pre-ordering of phrase-based machine translation input in translation workflow—0
Preparation of Sentiment tagged Parallel Corpus and Testing its effect on Machine Translation—0
Prepositional Attachment Disambiguation Using Bilingual Parsing and Alignments—0
Pre-processing and Language Analysis for Arabic to French Statistical Machine Translation (Traduction automatique statistique pour l'arabe-fran am\'elior\'ee par le pr\'etraitement et l'analyse de la langue) [in French]—0
Pre-Reordering for Machine Translation Using Transition-Based Walks on Dependency Parse Trees—0
Pre-reordering for Statistical Machine Translation of Non-fictional Subtitles—0
Pre-reordering Model of Chinese Special Sentences for Patent Machine Translation—0
PRESEMT: Pattern Recognition-based Statistically Enhanced MT—0
Preservation of Recognizability for Weighted Linear Extended Top-Down Tree Transducers—0
Pre-trained Language Model Representations for Language Generation—0
Pretrained Language Models and Backtranslation for English-Basque Biomedical Neural Machine Translation—0
Pretrained Language Models for Document-Level Neural Machine Translation—0
Pre-Trained Multilingual Sequence-to-Sequence Models: A Hope for Low-Resource Language Translation?—0
Pre-training Methods for Neural Machine Translation—0
Pre-training Synthetic Cross-lingual Decoder for Multilingual Samples Adaptation in E-Commerce Neural Machine Translation—0
Pre-training via Leveraging Assisting Languages and Data Selection for Neural Machine Translation—0
Pre-training via Leveraging Assisting Languages for Neural Machine Translation—0
Pre-Translation for Neural Machine Translation—0
PRHLT Submission to the WMT12 Quality Estimation Task—0
Priming Ancient Korean 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