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 6201–6250 of 10752 papers

TitleStatusHype
Experiments with Easy-first nonprojective constituent parsing—0
Experiments with Generative Models for Dependency Tree Linearization—0
Experiments with POS-based restructuring and alignment-based reordering for statistical machine translation—0
Experiments with Term Translation—0
Explainable Deep RDFS Reasoner—0
Explaining and Generalizing Back-Translation through Wake-Sleep—0
Explaining Sequence-Level Knowledge Distillation as Data-Augmentation for Neural Machine Translation—0
Explicit Cross-lingual Pre-training for Unsupervised Machine Translation—0
Explicit Reordering for Neural Machine Translation—0
Exploiting a Large Strongly Comparable Corpus—0
Exploiting Bilingual Translation for Question Retrieval in Community-Based Question Answering—0
Exploiting Common Characters in Chinese and Japanese to Learn Cross-Lingual Word Embeddings via Matrix Factorization—0
Exploiting Deep Representations for Neural Machine Translation—0
Exploiting Domain-Specific Parallel Data on Multilingual Language Models for Low-resource Language Translation—0
Exploiting Language Models for Visual Recognition—0
Exploiting Language Relatedness in Machine Translation Through Domain Adaptation Techniques—0
Exploiting Linguistic Resources for Neural Machine Translation Using Multi-task Learning—0
Exploiting Monolingual Data at Scale for Neural Machine Translation—0
Exploiting Multilingualism in Low-resource Neural Machine Translation via Adversarial Learning—0
Exploiting Multilingualism through Multistage Fine-Tuning for Low-Resource Neural Machine Translation—0
Exploiting N-Best Hypotheses to Improve an SMT Approach to Grammatical Error Correction—0
Exploiting Neural Query Translation into Cross Lingual Information Retrieval—0
Exploiting Non-Taxonomic Relations for Measuring Semantic Similarity and Relatedness in WordNet—0
Exploiting Out-of-Domain Data Sources for Dialectal Arabic Statistical Machine Translation—0
Exploiting Parallel Corpus for Handling Out-of-Vocabulary Words—0
Exploiting portability to build an RBMT prototype for a new source language—0
Exploiting Pre-Ordering for Neural Machine Translation—0
Exploiting Qualitative Information from Automatic Word Alignment for Cross-lingual NLP Tasks—0
Exploiting Semantics in Neural Machine Translation with Graph Convolutional Networks—0
Exploiting Sentential Context for Neural Machine Translation—0
Exploiting Source-side Monolingual Data in Neural Machine Translation—0
Exploiting Transliterated Words for Finding Similarity in Inter-Language News Articles using Machine Learning—0
Exploration of Inter- and Intralingual Variation of Discourse Phenomena—0
Exploration of Neural Machine Translation in Autoformalization of Mathematics in Mizar—0
Exploring Adequacy Errors in Neural Machine Translation with the Help of Cross-Language Aligned Word Embeddings—0
Exploring Automatic Evaluation Methods based on a Decoder-based LLM for Text Generation—0
Exploring Benefits of Transfer Learning in Neural Machine Translation—0
Exploring Consensus in Machine Translation for Quality Estimation—0
Exploring Coreference Features in Heterogeneous Data—0
Exploring cross-language statistical machine translation for closely related South Slavic languages—0
Exploring Cross-Lingual Transfer Learning with Unsupervised Machine Translation—0
Exploring Distributional Representations and Machine Translation for Aspect-based Cross-lingual Sentiment Classification.—0
Exploring External Knowledge for Accurate modeling of Visual and Language Problems—0
Exploring Gap Filling as a Cheaper Alternative to Reading Comprehension Questionnaires when Evaluating Machine Translation for Gisting—0
Exploring Grammatical Error Correction with Not-So-Crummy Machine Translation—0
Exploring Hyper-Parameter Optimization for Neural Machine Translation on GPU Architectures—0
Exploring Hypotheses Spaces in Neural Machine Translation—0
Exploring Kernel Functions in the Softmax Layer for Contextual Word Classification—0
Exploring Linguistic Similarity and Zero-Shot Learning for Multilingual Translation of Dravidian Languages—0
Exploring Looping Effects in RNN-based Architectures—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