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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 10551–10600 of 10752 papers

TitleStatusHype
When Does Translation Require Context? A Data-driven, Multilingual Exploration—0
When Does Translation Require Context? A Data-driven, Multilingual Exploration—0
When Does Unsupervised Machine Translation Work?—0
When End-to-End is Overkill: Rethinking Cascaded Speech-to-Text Translation—0
Zero Alignment of Verb Arguments in a Parallel Treebank—0
When is Char Better Than Subword: A Systematic Study of Segmentation Algorithms for Neural Machine Translation—0
When less is more in Neural Quality Estimation of Machine Translation. An industry case study—0
When LLMs Struggle: Reference-less Translation Evaluation for Low-resource Languages—0
When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method—0
When to Finish? Optimal Beam Search for Neural Text Generation (modulo beam size)—0
The Parallel-TUT: a multilingual and multiformat treebank—0
The Post-Editing Workflow: Training Challenges for LSPs, Post-Editors and Academia—0
The Potential of AutoML for Recommender Systems—0
The power of Prompts: Evaluating and Mitigating Gender Bias in MT with LLMs—0
The Progression of Transformers from Language to Vision to MOT: A Literature Review on Multi-Object Tracking with Transformers—0
The Punster's Amanuensis: The Proper Place of Humans and Machines in the Translation of Wordplay—0
The QT21 Combined Machine Translation System for English to Latvian—0
The QT21/HimL Combined Machine Translation System—0
The Reality of Multi-Lingual Machine Translation—0
The Recent Advances in Automatic Term Extraction: A survey—0
There is no Artificial General Intelligence—0
Where does In-context Translation Happen in Large Language Models—0
The Representation of Czech Light Verb Constructions in a Valency Lexicon—0
The REPU CS’ Spanish–Quechua Submission to the AmericasNLP 2021 Shared Task on Open Machine Translation—0
There's no Data Like Better Data: Using QE Metrics for MT Data Filtering—0
The RGNLP Machine Translation Systems for WAT 2018—0
The role of artificially generated negative data for quality estimation of machine translation—0
The Role of Expectedness in the Implicitation and Explicitation of Discourse Relations—0
The Role of Handling Attributive Nouns in Improving Chinese-To-English Machine Translation—0
The Role of Modifier and Head Properties in Predicting the Compositionality of English and German Noun-Noun Compounds: A Vector-Space Perspective—0
The Role of n-gram Smoothing in the Age of Neural Networks—0
The RoyalFlush System for the WMT 2022 Efficiency Task—0
The RWTH Aachen German-English Machine Translation System for WMT 2015—0
The RWTH Aachen German-English Machine Translation System for WMT 2014—0
The RWTH Aachen Machine Translation System for WMT 2013—0
The RWTH Aachen Machine Translation System for WMT 2012—0
The RWTH Aachen Machine Translation System for IWSLT 2016—0
The RWTH Aachen Machine Translation Systems for IWSLT 2017—0
The RWTH Aachen University English-German and German-English Unsupervised Neural Machine Translation Systems for WMT 2018—0
The RWTH Aachen University English-German and German-English Machine Translation System for WMT 2017—0
The RWTH Aachen University English-Romanian Machine Translation System for WMT 2016—0
The RWTH Aachen University Filtering System for the WMT 2018 Parallel Corpus Filtering Task—0
The RWTH Aachen University Machine Translation Systems for WMT 2019—0
The RWTH Aachen University Supervised Machine Translation Systems for WMT 2018—0
The SADID Evaluation Datasets for Low-Resource Spoken Language Machine Translation of Arabic Dialects—0
The SAS Statistical Machine Translation System for WAT 2014—0
The Scielo Corpus: a Parallel Corpus of Scientific Publications for Biomedicine—0
The SDL Language Weaver Systems in the WMT12 Quality Estimation Shared Task—0
The Second QALB Shared Task on Automatic Text Correction for Arabic—0
The Set Autoencoder: Unsupervised Representation Learning for Sets—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
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