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 6301–6350 of 10752 papers

TitleStatusHype
Meaningless yet meaningful: Morphology grounded subword-level NMT—0
Literal, Metphorical or Both? Detecting Metaphoricity in Isolated Adjective-Noun Phrases—0
Unsupervised Detection of Metaphorical Adjective-Noun Pairs—0
Lexical Conceptual Structure of Literal and Metaphorical Spatial Language: A Case Study of ``Push''—0
On the Utility of Lay Summaries and AI Safety Disclosures: Toward Robust, Open Research Oversight—0
Language Model Based Grammatical Error Correction without Annotated Training Data—0
Neural Metaphor Detecting with CNN-LSTM Model—0
Phrase-Level Metaphor Identification Using Distributed Representations of Word Meaning—0
Cross-Lingual Content Scoring—0
Complex Word Identification Using Character n-grams—0
PAWS: A Multi-lingual Parallel Treebank with Anaphoric Relations—0
Multiplicative Tree-Structured Long Short-Term Memory Networks for Semantic Representations—0
ALB at SemEval-2018 Task 10: A System for Capturing Discriminative Attributes—0
EXPR at SemEval-2018 Task 9: A Combined Approach for Hypernym Discovery—0
ECNU at SemEval-2018 Task 10: Evaluating Simple but Effective Features on Machine Learning Methods for Semantic Difference Detection—0
SNU\_IDS at SemEval-2018 Task 12: Sentence Encoder with Contextualized Vectors for Argument Reasoning ComprehensionCode0
NTU NLP Lab System at SemEval-2018 Task 10: Verifying Semantic Differences by Integrating Distributional Information and Expert Knowledge—0
YNU Deep at SemEval-2018 Task 12: A BiLSTM Model with Neural Attention for Argument Reasoning Comprehension—0
ITNLP-ARC at SemEval-2018 Task 12: Argument Reasoning Comprehension with Attention—0
Graph Algebraic Combinatory Categorial Grammar—0
YNU\_Deep at SemEval-2018 Task 11: An Ensemble of Attention-based BiLSTM Models for Machine Comprehension—0
From dictations to clinical reports using machine translation—0
Combining Character and Word Information in Neural Machine Translation Using a Multi-Level Attention—0
What we need to learn if we want to do and not just talk—0
Using Word Vectors to Improve Word Alignments for Low Resource Machine Translation—0
Vis-Eval Metric Viewer: A Visualisation Tool for Inspecting and Evaluating Metric Scores of Machine Translation Output—0
Noising and Denoising Natural Language: Diverse Backtranslation for Grammar Correction—0
Evaluating bilingual word embeddings on the long tailCode0
Efficient Sequence Learning with Group Recurrent Networks—0
Quality Estimation for Automatically Generated Titles of eCommerce Browse Pages—0
QuickEdit: Editing Text \& Translations by Crossing Words Out—0
SemEval 2018 Task 4: Character Identification on Multiparty Dialogues—0
LSDSCC: a Large Scale Domain-Specific Conversational Corpus for Response Generation with Diversity Oriented Evaluation Metrics—0
Target Foresight Based Attention for Neural Machine Translation—0
Dialog Generation Using Multi-Turn Reasoning Neural Networks—0
Neural Poetry Translation—0
Learning Hidden Unit Contribution for Adapting Neural Machine Translation Models—0
A Comparison of Two Paraphrase Models for Taxonomy Augmentation—0
Deep Learning Approaches to Text Production—0
Practical Application of Domain Dependent Confidence Measurement for Spoken Language Understanding Systems—0
Automated Paraphrase Lattice Creation for HyTER Machine Translation Evaluation—0
Semantic Pleonasm Detection—0
Specialising Word Vectors for Lexical EntailmentCode0
Cross-Lingual Learning-to-Rank with Shared Representations—0
attr2vec: Jointly Learning Word and Contextual Attribute Embeddings with Factorization Machines—0
Cross-Domain Review Helpfulness Prediction Based on Convolutional Neural Networks with Auxiliary Domain Discriminators—0
Igbo Diacritic Restoration using Embedding Models—0
How Time Matters: Learning Time-Decay Attention for Contextual Spoken Language Understanding in DialoguesCode0
Context Sensitive Neural Lemmatization with Lematus—0
Higher-Order Syntactic Attention Network for Longer Sentence Compression—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