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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 9751–9800 of 10752 papers

TitleStatusHype
Toward Universal Dependencies for Shipibo-Konibo—0
Toward verbalizing ontologies in isiZulu—0
Toxicity in Multilingual Machine Translation at Scale—0
Toxic Subword Pruning for Dialogue Response Generation on Large Language Models—0
The Multilingual Microblog Translation Corpus: Improving and Evaluating Translation of User-Generated Text—0
TQ-AutoTest -- An Automated Test Suite for (Machine) Translation Quality—0
TQDL: Integrated Models for Cross-Language Document Retrieval—0
Traditional Machine Learning and Deep Learning Models for Argumentation Mining in Russian Texts—0
Traduction automatique \`a partir de corpus comparables: extraction de phrases parall\`eles \`a partir de donn\'ees comparables multimodales (Automatic Translation from Comparable corpora : extracting parallel sentences from multimodal comparable corpora) [in French]—0
Traduction automatique du japonais vers le fran Bilan et perspectives (Machine Translation from Japanese to French - Review and Prospects)—0
Traffic transformer: Capturing the continuity and periodicity of time series for traffic forecasting—0
Zero-Resource Neural Machine Translation with Monolingual Pivot Data—0
Train Big, Then Compress: Rethinking Model Size for Efficient Training and Inference of Transformers—0
Training a Bilingual Language Model by Mapping Tokens onto a Shared Character Space—0
The IMAGACT4ALL Ontology of Animated Images: Implications for Theoretical and Machine Translation of Action Verbs from English-Indian Languages—0
Training and Inference Methods for High-Coverage Neural Machine Translation—0
Training and Meta-Evaluating Machine Translation Evaluation Metrics at the Paragraph Level—0
With or without post-editing processes? Evidence for a gap in machine translation evaluation—0
Training Data is More Valuable than You Think: A Simple and Effective Method by Retrieving from Training Data—0
The MLLP-UPV Supervised Machine Translation Systems for WMT19 News Translation Task—0
With or without you? Effects of using machine translation to write flash fiction in the foreign language—0
Training Deep Networks with Stochastic Gradient Normalized by Layerwise Adaptive Second Moments—0
The MLLP-UPV Spanish-Portuguese and Portuguese-Spanish Machine Translation Systems for WMT19 Similar Language Translation Task—0
Training Flexible Depth Model by Multi-Task Learning for Neural Machine Translation—0
Without Further Ado: Direct and Simultaneous Speech Translation by AppTek in 2021—0
Training in translation tools and technologies: Findings of the EMT survey 2023—0
The MLLP-UPV German-English Machine Translation System for WMT18—0
Training Mixed-Domain Translation Models via Federated Learning—0
Training MRF-Based Phrase Translation Models using Gradient Ascent—0
Training Multilingual Machine Translation by Alternately Freezing Language-Specific Encoders-Decoders—0
Training Neural Machine Translation (NMT) Models using Tensor Train Decomposition on TensorFlow (T3F)—0
WMDO: Fluency-based Word Mover's Distance for Machine Translation Evaluation—0
Training Neural Machine Translation using Word Embedding-based Loss—0
Training on Synthetic Noise Improves Robustness to Natural Noise in Machine Translation—0
WMT2016: A Hybrid Approach to Bilingual Document Alignment—0
The ML4HMT Workshop on Optimising the Division of Labour in Hybrid Machine Translation—0
Training with Adversaries to Improve Faithfulness of Attention in Neural Machine Translation—0
The MITLL-AFRL IWSLT 2016 Systems—0
Train Once, and Decode As You Like—0
Trait-Based Hypothesis Selection For Machine Translation—0
TransBank: Metadata as the Missing Link between NLP and Traditional Translation Studies—0
TransBench: Benchmarking Machine Translation for Industrial-Scale Applications—0
TRANS-BLSTM: Transformer with Bidirectional LSTM for Language Understanding—0
TransChat: Cross-Lingual Instant Messaging for Indian Languages—0
TranscRater: a Tool for Automatic Speech Recognition Quality Estimation—0
Transcribing and Translating, Fast and Slow: Joint Speech Translation and Recognition—0
Trans-dimensional Random Fields for Language Modeling—0
WMT 2016 Multimodal Translation System Description based on Bidirectional Recurrent Neural Networks with Double-Embeddings—0
TransDoop: A Map-Reduce based Crowdsourced Translation for Complex Domain—0
Transductive Adaptation of Black Box Predictions—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