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 4451–4500 of 10752 papers

TitleStatusHype
Language-aware Interlingua for Multilingual Neural Machine Translation—0
ISTIC's Neural Machine Translation System for IWSLT'2020—0
Checkpoint Reranking: An Approach to Select Better Hypothesis for Neural Machine Translation Systems—0
Octanove Labs' Japanese-Chinese Open Domain Translation System—0
Improving Document-Level Neural Machine Translation with Domain Adaptation—0
Character Mapping and Ad-hoc Adaptation: Edinburgh's IWSLT 2020 Open Domain Translation System—0
The AFRL IWSLT 2020 Systems: Work-From-Home Edition—0
Exploring Model Consensus to Generate Translation ParaphrasesCode0
CASIA's System for IWSLT 2020 Open Domain Translation—0
Training and Inference Methods for High-Coverage Neural Machine Translation—0
Pre-training via Leveraging Assisting Languages for Neural Machine Translation—0
Improving Neural Machine Translation with Soft Template Prediction—0
Multi-Hypothesis Machine Translation Evaluation—0
Multitask Models for Controlling the Complexity of Neural Machine Translation—0
Multi-Task Neural Model for Agglutinative Language Translation—0
English-to-Japanese Diverse Translation by Combining Forward and Backward Outputs—0
End-to-End Offline Speech Translation System for IWSLT 2020 using Modality Agnostic Meta-Learning—0
Boosting Neural Machine Translation with Similar Translations—0
Efficient Neural Machine Translation for Low-Resource Languages via Exploiting Related Languages—0
Multimodal Quality Estimation for Machine Translation—0
Jointly Masked Sequence-to-Sequence Model for Non-Autoregressive Neural Machine Translation—0
Efficient and High-Quality Neural Machine Translation with OpenNMT—0
Effectively Aligning and Filtering Parallel Corpora under Sparse Data Conditions—0
Towards Understanding ASR Error Correction for Medical Conversations—0
BIT's system for the AutoSimTrans 2020—0
Edinburgh's Submissions to the 2020 Machine Translation Efficiency Task—0
Start-Before-End and End-to-End: Neural Speech Translation by AppTek and RWTH Aachen University—0
Document Translation vs. Query Translation for Cross-Lingual Information Retrieval in the Medical Domain—0
An Evaluation of Subword Segmentation Strategies for Neural Machine Translation of Morphologically Rich Languages—0
Towards Stream Translation: Adaptive Computation Time for Simultaneous Machine Translation—0
SIGMORPHON 2020 Task 0 System Description: ETH Z\"urich Team—0
Metaphor Detection Using Contextual Word Embeddings From Transformers—0
Tagged Back-translation Revisited: Why Does It Really Work?—0
Improving Autoregressive NMT with Non-Autoregressive Model—0
Robust Neural Machine Translation with ASR Errors—0
Translationese as a Language in ``Multilingual'' NMT—0
Automatic Machine Translation Evaluation using Source Language Inputs and Cross-lingual Language Model—0
``You Sound Just Like Your Father'' Commercial Machine Translation Systems Include Stylistic Biases—0
Automated Scoring of Clinical Expressive Language Evaluation Tasks—0
Uncertainty-Aware Curriculum Learning for Neural Machine Translation—0
Cross-Lingual Unsupervised Sentiment Classification with Multi-View Transfer Learning—0
The JHU Submission to the 2020 Duolingo Shared Task on Simultaneous Translation and Paraphrase for Language Education—0
LIT Team's System Description for Japanese-Chinese Machine Translation Task in IWSLT 2020—0
OPPO's Machine Translation System for the IWSLT 2020 Open Domain Translation Task—0
A Comparative Study of Synthetic Data Generation Methods for Grammatical Error Correction—0
Modeling Word Formation in English--German Neural Machine Translation—0
Addressing Posterior Collapse with Mutual Information for Improved Variational Neural Machine Translation—0
Towards Mitigating Gender Bias in a decoder-based Neural Machine Translation model by Adding Contextual Information—0
How Human is Machine Translationese? Comparing Human and Machine Translations of Text and Speech—0
A Mixture of h - 1 Heads is Better than h Heads—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