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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 8701–8750 of 10752 papers

TitleStatusHype
Neural Monkey: The Current State and Beyond—0
Neural Morphological Analysis: Encoding-Decoding Canonical Segments—0
Neural Morphological Tagging of Lemma Sequences for Machine Translation—0
Neural Name Translation Improves Neural Machine Translation—0
Neural Network Architectures for Arabic Dialect Identification—0
Neural Network Based Bilingual Language Model Growing for Statistical Machine Translation—0
Neural Network-Based Model for Japanese Predicate Argument Structure Analysis—0
Neural Network Language Models for Candidate Scoring in Hybrid Multi-System Machine Translation—0
Neural Networks for Multi-Word Expression Detection—0
Neural Networks For Negation Scope Detection—0
Neural Networks in a Product of Hyperbolic Spaces—0
Neural Network Transduction Models in Transliteration Generation—0
Neural Optimizer Search using Reinforcement Learning—0
Neural Paraphrase Generation using Transfer Learning—0
Neural Phrase-to-Phrase Machine Translation—0
Neural Poetry Translation—0
Neural Polysynthetic Language Modelling—0
Neural Post-Editing Based on Quality Estimation—0
Neural Pre-Translation for Hybrid Machine Translation—0
Neural Probabilistic Language Model for System Combination—0
Neural Program Planner for Structured Predictions—0
Neural Proto-Language Reconstruction—0
Neural Reordering Model Considering Phrase Translation and Word Alignment for Phrase-based Translation—0
Neural Reranking Improves Subjective Quality of Machine Translation: NAIST at WAT2015—0
Neural Response Generation via GAN with an Approximate Embedding Layer—0
Neural Semantic Parsing—0
Neural sentence generation from formal semantics—0
Neural Sequence-Labelling Models for Grammatical Error Correction—0
Neural Sequence Learning Models for Word Sense Disambiguation—0
Neural Sequence-to-sequence Learning of Internal Word Structure—0
Neural Simultaneous Speech Translation Using Alignment-Based Chunking—0
Neural Speech Translation at AppTek—0
Neural Speech Translation: From Neural Machine Translation to Direct Speech Translation—0
Neural-Symbolic Recursive Machine for Systematic Generalization—0
Neural System Combination for Machine Translation—0
Neural Text Generation: A Practical Guide—0
Neural Text Generation with Artificial Negative Examples—0
Neural Text Normalization with Subword Units—0
Neural Text Simplification in Low-Resource Conditions Using Weak Supervision—0
Neural Transition-based Parsing of Library Deprecations—0
Neural versus Phrase-Based Machine Translation Quality: a Case Study—0
Neural vs. Phrase-Based Machine Translation in a Multi-Domain Scenario—0
Neural Zero-Inflated Quality Estimation Model For Automatic Speech Recognition System—0
Neuron Interaction Based Representation Composition for Neural Machine Translation—0
Neuron Specialization: Leveraging intrinsic task modularity for multilingual machine translation—0
NeuroPrune: A Neuro-inspired Topological Sparse Training Algorithm for Large Language Models—0
New Approach to translation of Isolated Units in English-Korean Machine Translation—0
New Directions in Vector Space Models of Meaning—0
New Language Pairs in TectoMT—0
New language resources for the Pashto language—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