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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 4601–4650 of 10752 papers

TitleStatusHype
Lattice Desegmentation for Statistical Machine Translation—0
Lattice Transformer for Speech Translation—0
Latvian and Lithuanian Named Entity Recognition with TildeNER—0
LAYERED: Metric for Machine Translation Evaluation—0
Layers of Interpretation: On Grammar and Compositionality—0
Layer-Wise Coordination between Encoder and Decoder for Neural Machine Translation—0
Rethinking and Improving Natural Language Generation with Layer-Wise Multi-View Decoding—0
Layer-Wise Multi-View Learning for Neural Machine Translation—0
Layer-wise Regularized Dropout for Neural Language Models—0
Lazy Low-Resource Coreference Resolution: a Study on Leveraging Black-Box Translation Tools—0
LCP-dropout: Compression-based Multiple Subword Segmentation for Neural Machine Translation—0
LCQMC:A Large-scale Chinese Question Matching Corpus—0
LDC Language Resource Database: Building a Bibliographic Database—0
LEAPT: Learning Adaptive Prefix-to-prefix Translation For Simultaneous Machine Translation—0
Learning a bidirectional mapping between human whole-body motion and natural language using deep recurrent neural networks—0
Learning Accurate Integer Transformer Machine-Translation Models—0
Learning aligned embeddings for semi-supervised word translation using Maximum Mean Discrepancy—0
Learning Alternative Name Spellings—0
Learning a Multi-Domain Curriculum for Neural Machine Translation—0
Learning an Interactive Attention Policy for Neural Machine Translation—0
Learning a Phrase-based Translation Model from Monolingual Data with Application to Domain Adaptation—0
Learning attention for historical text normalization by learning to pronounce—0
Learning Better Rule Extraction with Translation Span Alignment—0
Learning Better Structured Representations Using Low-rank Adaptive Label Smoothing—0
Learning Bilingual Projections of Embeddings for Vocabulary Expansion in Machine Translation—0
Learning Bilingual Sentence Embeddings via Autoencoding and Computing Similarities with a Multilayer Perceptron—0
Learning Bilingual Sentiment Word Embeddings for Cross-language Sentiment Classification—0
Learning bilingual word embeddings with (almost) no bilingual data—0
Learning Compositional Semantics for Open Domain Semantic Parsing—0
Learning Contextualized Sentence Representations for Document-Level Neural Machine Translation—0
Learning Continuous Phrase Representations for Translation Modeling—0
Learning Coupled Policies for Simultaneous Machine Translation using Imitation Learning—0
Learning Cross-lingual Representations with Matrix Factorization—0
Learning Cross-lingual Word Embeddings via Matrix Co-factorization—0
Learning Curricula for Multilingual Neural Machine Translation Training—0
Learning Decoupled Retrieval Representation for Nearest Neighbour Neural Machine Translation—0
Learning Distributional Token Representations from Visual Features—0
Learning Domain Specific Language Models for Automatic Speech Recognition through Machine Translation—0
Learning Efficient Lexically-Constrained Neural Machine Translation with External Memory—0
Learning Ensembles of Structured Prediction Rules—0
Learning Feature Weights using Reward Modeling for Denoising Parallel Corpora—0
Learning from Chunk-based Feedback in Neural Machine Translation—0
Learning from Multiple Partially Observed Views - an Application to Multilingual Text Categorization—0
Learning from others' mistakes: Finetuning machine translation models with span-level error annotations—0
Learning from Parenthetical Sentences for Term Translation in Machine Translation—0
Learning from Post-Editing: Online Model Adaptation for Statistical Machine Translation—0
Learning from Relatives: Unified Dialectal Arabic Segmentation—0
Learning Hard Retrieval Decoder Attention for Transformers—0
Learning Hidden Unit Contribution for Adapting Neural Machine Translation Models—0
Learning Hierarchical Translation Spans—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