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

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Showing 5701–5750 of 10752 papers

TitleStatusHype
SRCB Neural Machine Translation Systems in WAT 2018—0
SRU++: Pioneering Fast Recurrence with Attention for Speech Recognition—0
SSA-COMET: Do LLMs Outperform Learned Metrics in Evaluating MT for Under-Resourced African Languages?—0
SSF: A Common Representation Scheme for Language Analysis for Language Technology Infrastructure Development—0
SSMT:A Machine Translation Evaluation View To Paragraph-to-Sentence Semantic Similarity—0
SSN-NLP at SemEval-2020 Task 4: Text Classification and Generation on Common Sense Context Using Neural Networks—0
StableMoE: Stable Routing Strategy for Mixture of Experts—0
STACC, OOV Density and N-gram Saturation: Vicomtech's Participation in the WMT 2018 Shared Task on Parallel Corpus Filtering—0
Stack-based Multi-layer Attention for Transition-based Dependency Parsing—0
Stacked Acoustic-and-Textual Encoding: Integrating the Pre-trained Models into Speech Translation Encoders—0
Stacking for Statistical Machine Translation—0
Stand-off Annotation of Web Content as a Legally Safer Alternative to Crawling for Distribution—0
Stanford: Probabilistic Edit Distance Metrics for STS—0
Stanford University's Submissions to the WMT 2014 Translation Task—0
Start-Before-End and End-to-End: Neural Speech Translation by AppTek and RWTH Aachen University—0
State of NLP in Kenya: A Survey—0
State Spaces Aren't Enough: Machine Translation Needs Attention—0
State-Split for Hypergraphs with an Application to Tree Adjoining Grammars—0
Statistical and Neural Methods for Cross-lingual Entity Label Mapping in Knowledge Graphs—0
Statistical-based System for Morphological Annotation of Arabic Texts—0
Statistical Machine Translation between Related Languages—0
Statistical Machine Translation between Myanmar (Burmese) and Dawei (Tavoyan)—0
Statistical Machine Translation Features with Multitask Tensor Networks—0
Statistical Machine Translation for Indian Languages: Mission Hindi 2—0
Statistical Machine Translation for Indian Languages: Mission Hindi—0
Statistical Machine Translation for Indic Languages—0
Statistical Machine Translation Improvement based on Phrase Selection—0
Statistical Machine Translation Improves Question Retrieval in Community Question Answering via Matrix Factorization—0
Statistical Machine Translation in Low Resource Settings—0
Statistical Machine Translation Using 5-grams Word Segmentation in Decoding—0
Statistical Machine Translation with Readability Constraints—0
Statistical Machine Translation with Automatic Identification of Translationese—0
Statistical Machine Translation without Source-side Parallel Corpus Using Word Lattice and Phrase Extension—0
Statistical Machine Transliteration Baselines for NEWS 2018—0
Statistical models for text normalization and machine translation—0
Statistical Morphological Analyzer for Hindi—0
Statistical Phrase-Based Translation—0
Statistical Power and Translationese in Machine Translation Evaluation—0
Statistical Sandhi Splitter and its Effect on NLP Applications—0
Statistical Vs Rule Based Machine Translation; A Case Study on Indian Language Perspective—0
Stay on topic with Classifier-Free Guidance—0
Steering Large Language Models for Machine Translation with Finetuning and In-Context Learning—0
Stem Translation with Affix-Based Rule Selection for Agglutinative Languages—0
Still not systematic after all these years: On the compositional skills of sequence-to-sequence recurrent networks—0
Stochastic Bi-Languages to model Dialogs—0
Story Generation from Sequence of Independent Short Descriptions—0
Strategies for Adapting Multilingual Pre-training for Domain-Specific Machine Translation—0
Strategy and Policy Learning for Non-Task-Oriented Conversational Systems—0
Strategy-Based Technology for Estimating MT Quality—0
Streaming Attention-Based Models with Augmented Memory for End-to-End Speech Recognition—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