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 1451–1500 of 10752 papers

TitleStatusHype
A Neural Network Approach to Context-Sensitive Generation of Conversational Responses—0
Basque and Spanish Counter Narrative Generation: Data Creation and Evaluation—0
Large Language Models for Classical Chinese Poetry Translation: Benchmarking, Evaluating, and Improving—0
A Neural Network based Approach to Automatic Post-Editing—0
Benchmarking Machine Translated Sentiment Analysis for Arabic Tweets—0
Adversarial Training with Contrastive Learning in NLP—0
Benchmarking Neural and Statistical Machine Translation on Low-Resource African Languages—0
A Neural Network Model for Low-Resource Universal Dependency Parsing—0
Benchmarking of English-Hindi parallel corpora—0
Benchmarking SMT Performance for Farsi Using the TEP++ Corpus—0
Benefiting from Language Similarity in the Multilingual MT Training: Case Study of Indonesian and Malaysian—0
Benefits of Data Augmentation for NMT-based Text Normalization of User-Generated Content—0
Bengali to Assamese Statistical Machine Translation using Moses (Corpus Based)—0
BERT Enhanced Neural Machine Translation and Sequence Tagging Model for Chinese Grammatical Error Diagnosis—0
Boosting the creation of a treebank—0
Boosting Unsupervised Machine Translation with Pseudo-Parallel Data—0
Bootstrapping a Hybrid MT System to a New Language Pair—0
BERTology for Machine Translation: What BERT Knows about Linguistic Difficulties for Translation—0
BERT-PersNER: A New Model for Persian Named Entity Recognition—0
Basic Principles for Segmenting Thai EDUs—0
BERT(s) to Detect Multiword Expressions—0
BERTTune: Fine-Tuning Neural Machine Translation with BERTScore—0
BERT vs GPT for financial engineering—0
Better Datastore, Better Translation: Generating Datastores from Pre-Trained Models for Nearest Neural Machine Translation—0
An Evaluation of Persian-English Machine Translation Datasets with Transformers—0
Better OOV Translation with Bilingual Terminology Mining—0
Better Quality Estimation for Low Resource Corpus Mining—0
Better Statistical Machine Translation through Linguistic Treatment of Phrasal Verbs—0
Better Together: Modern Methods Plus Traditional Thinking in NP Alignment—0
An entity-driven recursive neural network model for chinese discourse coherence modeling—0
Better Uncertainty Quantification for Machine Translation Evaluation—0
Boosting Neural Machine Translation with Similar Translations—0
Between Reading Time and Information Structure—0
A New Approach for Idiom Identification Using Meanings and the Web—0
A new approach to calculating BERTScore for automatic assessment of translation quality—0
Beyond BLEU:Training Neural Machine Translation with Semantic Similarity—0
Beyond Correlation: Interpretable Evaluation of Machine Translation Metrics—0
A New Massive Multilingual Dataset for High-Performance Language Technologies—0
Baseline Models for Pronoun Prediction and Pronoun-Aware Translation—0
An Entity-Centric Coreference Resolution System for Person Entities with Rich Linguistic Information—0
A New Parsing Algorithm for Combinatory Categorial Grammar—0
Beyond English: Evaluating LLMs for Arabic Grammatical Error Correction—0
Beyond Error Propagation in Neural Machine Translation: Characteristics of Language Also Matter—0
Adversarial Training on Disentangling Meaning and Language Representations for Unsupervised Quality Estimation—0
Beyond General Purpose Machine Translation: The Need for Context-specific Empirical Research to Design for Appropriate User Trust—0
Beyond Glass-Box Features: Uncertainty Quantification Enhanced Quality Estimation for Neural Machine Translation—0
A New Semantic Lexicon and Similarity Measure in Bangla—0
Beyond Human-Only: Evaluating Human-Machine Collaboration for Collecting High-Quality Translation Data—0
Beyond MLE: Investigating SEARNN for Low-Resourced Neural Machine Translation—0
Deps-SAN: Neural Machine Translation with Dependency-Scaled Self-Attention Network—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