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 2801–2850 of 10752 papers

TitleStatusHype
Disentangled Mask Attention in Transformer—0
Contrastive Clustering to Mine Pseudo Parallel Data for Unsupervised Translation—0
Target-Side Data Augmentation for Sequence GenerationCode1
Adaptive Label Smoothing with Self-Knowledge—0
Lagrangian Method for Episodic Learning—0
Translating Robot Skills: Learning Unsupervised Skill Correspondences Across Robots—0
On the Effectiveness of Quasi Character-Level Models for Machine Translation—0
Crossformer: Transformer with Alternated Cross-Layer Guidance—0
Non-Autoregressive Models are Better Multilingual Translators—0
Improving Non-Autoregressive Translation Models Without Distillation—0
TransSlowDown: Efficiency Attacks on Neural Machine Translation Systems—0
DictFormer: Tiny Transformer with Shared Dictionary—0
Gesture2Vec: Clustering Gestures using Representation Learning Methods for Co-speech Gesture GenerationCode1
DM-CT: Consistency Training with Data and Model Perturbation—0
To Smooth or not to Smooth? On Compatibility between Label Smoothing and Knowledge Distillation—0
BLEU, METEOR, BERTScore: Evaluation of Metrics Performance in Assessing Critical Translation Errors in Sentiment-oriented Text—0
EdinSaar@WMT21: North-Germanic Low-Resource Multilingual NMT—0
Text Simplification for Comprehension-based Question-AnsweringCode0
Cross-lingual Intermediate Fine-tuning improves Dialogue State TrackingCode0
Towards Reinforcement Learning for Pivot-based Neural Machine Translation with Non-autoregressive Transformer—0
Translating from Morphologically Complex Languages: A Paraphrase-Based Approach—0
Abstraction, Reasoning and Deep Learning: A Study of the "Look and Say" Sequence—0
Analyzing the Use of Character-Level Translation with Sparse and Noisy Datasets—0
Fast-MD: Fast Multi-Decoder End-to-End Speech Translation with Non-Autoregressive Hidden IntermediatesCode3
Integrated Training for Sequence-to-Sequence Models Using Non-Autoregressive Transformer—0
Curb Your Carbon Emissions: Benchmarking Carbon Emissions in Machine Translation—0
Improved statistical machine translation using monolingual paraphrases—0
Self-Enhancing Multi-filter Sequence-to-Sequence Model—0
Predicting Attention Sparsity in Transformers—0
Unsupervised Translation of German--Lower Sorbian: Exploring Training and Novel Transfer Methods on a Low-Resource LanguageCode0
GERNERMED -- An Open German Medical NER ModelCode1
Faithful Target Attribute Prediction in Neural Machine TranslationCode0
Non-Parametric Online Learning from Human Feedback for Neural Machine TranslationCode0
Exploiting Curriculum Learning in Unsupervised Neural Machine TranslationCode0
The NiuTrans Machine Translation Systems for WMT21—0
Scalable and Efficient MoE Training for Multitask Multilingual Models—0
Pushing the Right Buttons: Adversarial Evaluation of Quality EstimationCode0
Hierarchical Multimodal Transformer to Summarize Videos—0
Learning Domain Specific Language Models for Automatic Speech Recognition through Machine Translation—0
Multilingual Document-Level Translation Enables Zero-Shot Transfer From Sentences to Documents—0
One Source, Two Targets: Challenges and Rewards of Dual DecodingCode0
Learning Kernel-Smoothed Machine Translation with Retrieved ExamplesCode1
TranslateLocally: Blazing-fast translation running on the local CPU—0
MeetDot: Videoconferencing with Live Translation Captions—0
Adversarial Training with Contrastive Learning in NLP—0
Modeling Future for Neural Machine Translation by Fusing Target Information—0
Attention Mechanism with Energy-Friendly Operations—0
Digging Errors in NMT: Evaluating and Understanding Model Errors from Hypothesis Distribution—0
Contrastive Word Embedding Learning for Neural Machine Translation—0
Modeling Multi-granularity Segmentation for Rare Words 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