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 9301–9350 of 10752 papers

TitleStatusHype
Continuous Measurement Scales in Human Evaluation of Machine Translation—0
Continuous Model Improvement for Language Understanding with Machine Translation—0
Continuous multilinguality with language vectors—0
Continuous Profile Models in ASL Syntactic Facial Expression Synthesis—0
Continuous Space Translation Models for Phrase-Based Statistical Machine Translation—0
Continuous Space Translation Models with Neural Networks—0
Continuous Word Embedding Fusion via Spectral Decomposition—0
ContraCAT: Contrastive Coreference Analytical Templates for Machine Translation—0
Contractions: To Align or Not to Align, That Is the Question—0
Contractive error feedback for gradient compression—0
Contrastive Clustering to Mine Pseudo Parallel Data for Unsupervised Translation—0
Contrastive Conditional Masked Language Model for Non-autoregressive Neural Machine Translation—0
Contrastive Learning for Context-aware Neural Machine TranslationUsing Coreference Information—0
Contrastive Learning for Context-aware Neural Machine Translation Using Coreference Information—0
Contrastive Learning for Low Resource Machine Translation—0
Contrastive Token Learning with Similarity Decay for Repetition Suppression in Machine Translation—0
Contrastive Word Embedding Learning for Neural Machine Translation—0
ContrastScore: Towards Higher Quality, Less Biased, More Efficient Evaluation Metrics with Contrastive Evaluation—0
Contribution au Niveau de l'Approche Indirecte à Base de Transfert dans la Traduction Automatique—0
Controllable Text Generation for Open-Domain Creativity and Fairness—0
Controllable Time-Delay Transformer for Real-Time Punctuation Prediction and Disfluency Detection—0
Controlled Ascent: Imbuing Statistical MT with Linguistic Knowledge—0
Controlled Authoring In A Hybrid Russian-English Machine Translation System—0
Controlling Extra-Textual Attributes about Dialogue Participants -- A Case Study of English-to-Polish Neural Machine Translation—0
Controlling Extra-Textual Attributes about Dialogue Participants: A Case Study of English-to-Polish Neural Machine Translation—0
Controlling Human Perception of Basic User Traits—0
Controlling Japanese Honorifics in English-to-Japanese Neural Machine Translation—0
Controlling Machine Translation for Multiple Attributes with Additive Interventions—0
Controlling Politeness in Neural Machine Translation via Side Constraints—0
Controlling Target Features in Neural Machine Translation via Prefix Constraints—0
Controlling the Output Length of Neural Machine Translation—0
Controlling the Reading Level of Machine Translation Output—0
Controlling the Voice of a Sentence in Japanese-to-English Neural Machine Translation—0
Controlling Utterance Length in NMT-based Word Segmentation with Attention—0
Conversational SimulMT: Efficient Simultaneous Translation with Large Language Models—0
Converting Continuous-Space Language Models into N-Gram Language Models for Statistical Machine Translation—0
Converting Epics/Stories into Pseudocode using Transformers—0
Converting Phrase Structures to Dependency Structures in Sanskrit—0
Converting Russian Dependency Treebank to Stanford Typed Dependencies Representation—0
Convolutional Self-Attention Networks—0
Convolution-Enhanced Bilingual Recursive Neural Network for Bilingual Semantic Modeling—0
Convolutions Are All You Need (For Classifying Character Sequences)—0
Cool English: a Grammatical Error Correction System Based on Large Learner Corpora—0
Coordinate System Selection for Minimum Error Rate Training in Statistical Machine Translation—0
Coordination Structures in Dependency Treebanks—0
Copied Monolingual Data Improves Low-Resource Neural Machine Translation—0
Coping with the Subjectivity of Human Judgements in MT Quality Estimation—0
Coreference and Coherence in Neural Machine Translation: A Study Using Oracle Experiments—0
Coreference by Appearance: Visually Grounded Event Coreference Resolution—0
Co-reference Resolution of Elided Subjects and Possessive Pronouns in Spanish-English Statistical Machine Translation—0
Show:102550
← PrevPage 187 of 216Next →
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