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 3951–4000 of 10752 papers

TitleStatusHype
Cross-lingual sentiment classification in low-resource Bengali languageCode0
A Semi-supervised Approach to Generate the Code-Mixed Text using Pre-trained Encoder and Transfer Learning—0
Vocabulary Adaptation for Domain Adaptation in Neural Machine TranslationCode0
Simultaneous Translation—0
Factorized Transformer for Multi-Domain Neural Machine Translation—0
Looking inside Noun Compounds: Unsupervised Prepositional and Free Paraphrasing—0
Relations between comprehensibility and adequacy errors in machine translation output—0
Active Learning Approaches to Enhancing Neural Machine Translation—0
Multi-Agent Mutual Learning at Sentence-Level and Token-Level for Neural Machine Translation—0
Using Visual Feature Space as a Pivot Across LanguagesCode0
Assessing Human-Parity in Machine Translation on the Segment Level—0
From Disjoint Sets to Parallel Data to Train Seq2Seq Models for Sentiment Transfer—0
Revisiting Representation Degeneration Problem in Language Modeling—0
Hybrid Emoji-Based Masked Language Models for Zero-Shot Abusive Language Detection—0
Effective Deep Learning Models for Automatic Diacritization of Arabic TextCode1
Statistical Power and Translationese in Machine Translation Evaluation—0
Alignment-free Cross-lingual Semantic Role Labeling—0
Improving Word Sense Disambiguation with Translations—0
Coding Textual Inputs Boosts the Accuracy of Neural NetworksCode0
Losing Heads in the Lottery: Pruning Transformer Attention in Neural Machine Translation—0
Monolingual Adapters for Zero-Shot Neural Machine Translation—0
Effectively pretraining a speech translation decoder with Machine Translation data—0
Distilling Multiple Domains for Neural Machine Translation—0
Direct Segmentation Models for Streaming Speech TranslationCode0
Towards Enhancing Faithfulness for Neural Machine Translation—0
CSP:Code-Switching Pre-training for Neural Machine Translation—0
Tilde at WMT 2020: News Task Systems—0
The Volctrans Machine Translation System for WMT20—0
Fast Interleaved Bidirectional Sequence Generation—0
Exploiting Neural Query Translation into Cross Lingual Information Retrieval—0
Data Troubles in Sentence Level Confidence Estimation for Machine Translation—0
Curious Case of Language Generation Evaluation Metrics: A Cautionary Tale—0
Constraint Translation Candidates: A Bridge between Neural Query Translation and Cross-lingual Information Retrieval—0
Is it Great or Terrible? Preserving Sentiment in Neural Machine Translation of Arabic Reviews—0
The LMU Munich System for the WMT 2020 Unsupervised Machine Translation Shared TaskCode0
RMHIDD: A Reddit Mental Health Intervention Dialogue Dataset—0
On Learning Text Style Transfer with Direct RewardsCode0
Multi-Task Learning with Shared Encoder for Non-Autoregressive Machine TranslationCode1
Unsupervised Vision-and-Language Pre-training Without Parallel Images and CaptionsCode1
Pre-trained Summarization DistillationCode0
Context-aware Decoder for Neural Machine Translation using a Target-side Document-Level Language Model—0
Rapid Domain Adaptation for Machine Translation with Monolingual Data—0
LightSeq: A High Performance Inference Library for TransformersCode2
Concealed Data Poisoning Attacks on NLP Models—0
N-ODE Transformer: A Depth-Adaptive Variant of the Transformer Using Neural Ordinary Differential EquationsCode0
CUNI Systems for the Unsupervised and Very Low Resource Translation Task in WMT20—0
Not all parameters are born equal: Attention is mostly what you needCode0
XOR QA: Cross-lingual Open-Retrieval Question AnsweringCode1
On the Potential of Lexico-logical Alignments for Semantic Parsing to SQL QueriesCode1
A General Multi-Task Learning Framework to Leverage Text Data for Speech to Text Tasks—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