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 3551–3600 of 10752 papers

TitleStatusHype
Understanding Pre-Editing for Black-Box Neural Machine Translation—0
One Size Does Not Fit All: Finding the Optimal Subword Sizes for FastText Models across Languages—0
Two Demonstrations of the Machine Translation Applications to Historical DocumentsCode0
Gamified Crowdsourcing for Idiom Corpora ConstructionCode0
[Re] Reproducing Learning to Deceive With Attention-Based ExplanationsCode0
Machine Translationese: Effects of Algorithmic Bias on Linguistic Complexity in Machine Translation—0
Enhancing the Transformer Decoder with Transition-based SyntaxCode0
Synthesizing Monolingual Data for Neural Machine Translation—0
A Comparison of Approaches to Document-level Machine Translation—0
Neural machine translation, corpus and frugality—0
Disambiguating Symbolic Expressions in Informal Documents—0
Cross-lingual Visual Pre-training for Multimodal Machine TranslationCode1
Facilitating Terminology Translation with Target Lemma AnnotationsCode0
Towards a Better Integration of Fuzzy Matches in Neural Machine Translation through Data AugmentationCode1
Fast Sequence Generation with Multi-Agent Reinforcement Learning—0
Towards Natural Language Question Answering over Earth Observation Linked Data using Attention-based Neural Machine Translation—0
Enriching Non-Autoregressive Transformer with Syntactic and SemanticStructures for Neural Machine Translation—0
GENIE: Toward Reproducible and Standardized Human Evaluation for Text GenerationCode0
To Understand Representation of Layer-aware Sequence Encoders as Multi-order-graph—0
Empirical Evaluation of Supervision Signals for Style Transfer Models—0
Recent Advances in Video Question Answering: A Review of Datasets and Methods—0
The Impact of Post-editing and Machine Translation on Creativity and Reading ExperienceCode0
Context- and Sequence-Aware Convolutional Recurrent Encoder for Neural Machine Translation—0
A Reinforcement Learning Based Encoder-Decoder Framework for Learning Stock Trading RulesCode1
A Novel Word Sense Disambiguation Approach Using WordNet Knowledge Graph—0
AutoDropout: Learning Dropout Patterns to Regularize Deep Networks—0
An Efficient Transformer Decoder with Compressed Sub-layers—0
The Highs and Lows of Simple Lexical Domain Adaptation Approaches for Neural Machine Translation—0
Graphmax for Text Generation—0
Subformer: Exploring Weight Sharing for Parameter Efficiency in Generative TransformersCode1
Improving Machine Translation by Searching Skip Connections Efficiently—0
Switching-Aligned-Words Data Augmentation for Neural Machine Translation—0
Efficient Neural Machine Translation with Prior Word Alignment—0
Recurrently Controlling a Recurrent Network with Recurrent Networks Controlled by More Recurrent Networks—0
Predictive Attention Transformer: Improving Transformer with Attention Map Prediction—0
Knowledge Distillation based Ensemble Learning for Neural Machine Translation—0
Towards Practical Second Order Optimization for Deep Learning—0
PhraseTransformer: Self-Attention using Local Context for Semantic ParsingCode0
Crowd-sourced Phrase-Based Tokenization for Low-Resourced Neural Machine Translation: The case of Fon Language—0
Cross-lingual Transfer Learning for Pre-trained Contextualized Language Models—0
Translation Memory Guided Neural Machine Translation—0
Parameterization of Hypercomplex Multiplications—0
Towards Principled Representation Learning for Entity Alignment—0
A Simple and General Strategy for Referential Problem in Low-Resource Neural Machine Translation—0
Good for Misconceived Reasons: Revisiting Neural Multimodal Machine Translation—0
N-Bref : A High-fidelity Decompiler Exploiting Programming StructuresCode1
Subformer: A Parameter Reduced Transformer—0
LLBoost: Last Layer Perturbation to Boost Pre-trained Neural Networks—0
Learning Better Structured Representations Using Low-rank Adaptive Label Smoothing—0
DiP Benchmark Tests: Evaluation Benchmarks for Discourse Phenomena in MT—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
5AdminBLEU score43.8—Unverified
6Transformer (ADMIN init)BLEU 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