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 5451–5500 of 10752 papers

TitleStatusHype
Multimodal Machine Translation through Visuals and Speech—0
Multimodal Machine Translation with Reinforcement Learning—0
Multimodal Machine Translation with Visual Scene Graph Pruning—0
Multimodal Neural Machine Translation for English to Hindi—0
Multimodal Neural Machine Translation for Low-resource Language Pairs using Synthetic Data—0
Multimodal Neural Machine Translation System for English to Bengali—0
Multimodal Neural Machine Translation with Search Engine Based Image Retrieval—0
Multimodal Pivots for Image Caption Translation—0
Multimodal Quality Estimation for Machine Translation—0
Multi-Modal Representations for Improved Bilingual Lexicon Learning—0
Multimodal Simultaneous Machine Translation—0
Multimodal Transformer with Multi-View Visual Representation for Image Captioning—0
Multi-modular domain-tailored OCR post-correction—0
Multi-Module Recurrent Neural Networks with Transfer Learning—0
MultiNews: A Web collection of an Aligned Multimodal and Multilingual Corpus—0
Multi-paraphrase Augmentation to Leverage Neural Caption Translation—0
Multi-Pass Decoding With Complex Feature Guidance for Statistical Machine Translation—0
Multi-Pass Transformer for Machine Translation—0
Multi-Path Transformer is Better: A Case Study on Neural Machine Translation—0
Multi-perspective Alignment for Increasing Naturalness in Neural Machine Translation—0
Multi-Perspective Sentence Similarity Modeling with Convolutional Neural Networks—0
Multiple Captions Embellished Multilingual Multi-Modal Neural Machine Translation—0
Multiple Pivot Languages and Strategic Decoder Initialization Helps Neural Machine Translation—0
Multiple References with Meaningful Variations Improve Literary Machine Translation—0
Multiple Segmentations of Thai Sentences for Neural Machine Translation—0
Multiple System Combination for Transliteration—0
Multiplicative Tree-Structured Long Short-Term Memory Networks for Semantic Representations—0
Multi-Predicate Semantic Role Labeling—0
Multi-Rate HMMs for Word Alignment—0
Multi-Reference Evaluation for Dialectal Speech Recognition System: A Study for Egyptian ASR—0
Multi-Reference Training with Pseudo-References for Neural Translation and Text Generation—0
Multi-representation Ensembles and Delayed SGD Updates Improve Syntax-based NMT—0
Multiresolution Transformer Networks: Recurrence is Not Essential for Modeling Hierarchical Structure—0
Multi-Reward based Reinforcement Learning for Neural Machine Translation—0
MultiSlav: Using Cross-Lingual Knowledge Transfer to Combat the Curse of Multilinguality—0
Multi-source Neural Automatic Post-Editing: FBK's participation in the WMT 2017 APE shared task—0
Multi-Source Neural Machine Translation with Missing Data—0
Multi-Source Neural Machine Translation with Data Augmentation—0
Multi-Source Syntactic Neural Machine Translation—0
Multi-Source Transformer for Kazakh-Russian-English Neural Machine Translation—0
Multi-source transformer with combined losses for automatic post editing—0
Multi-split Reversible Transformers Can Enhance Neural Machine Translation—0
Multi-Stage Framework with Refinement based Point Set Registration for Unsupervised Bi-Lingual Word Alignment—0
Multi-Stage Framework with Refinement Based Point Set Registration for Unsupervised Bi-Lingual Word Alignment—0
Multi-Target Machine Translation with Multi-Synchronous Context-free Grammars—0
Multitask Finetuning for Improving Neural Machine Translation in Indian Languages—0
Multi-Task Learning for Cross-Lingual Abstractive Summarization—0
Multitask Learning For Different Subword Segmentations In Neural Machine Translation—0
Multi-Task Learning for Improved Discriminative Training in SMT—0
Multi-Task Learning for Improving Gender Accuracy in Neural Machine Translation—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