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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 2501–2550 of 10752 papers

TitleStatusHype
BERT(s) to Detect Multiword Expressions—0
Fast Vocabulary Projection Method via Clustering for Multilingual Machine Translation on GPU—0
Structural Biases for Improving Transformers on Translation into Morphologically Rich Languages—0
How Effective is Byte Pair Encoding for Out-Of-Vocabulary Words in Neural Machine Translation?—0
Model Blending for Text Classification—0
Momentum Transformer: Closing the Performance Gap Between Self-attention and Its Linearization—0
Neural Knowledge Bank for Pretrained Transformers—0
Mismatching-Aware Unsupervised Translation Quality Estimation For Low-Resource LanguagesCode0
GTrans: Grouping and Fusing Transformer Layers for Neural Machine TranslationCode0
Thutmose Tagger: Single-pass neural model for Inverse Text Normalization—0
Benchmarking Azerbaijani Neural Machine Translation—0
Neural Architecture Search on Efficient Transformers and Beyond—0
Sequence to sequence pretraining for a less-resourced Slovenian languageCode0
Multimodal Neural Machine Translation with Search Engine Based Image Retrieval—0
Lagrangian Method for Q-Function Learning (with Applications to Machine Translation)—0
MoEC: Mixture of Expert Clusters—0
MAD for Robust Reinforcement Learning in Machine Translation—0
Open Terminology Management and Sharing Toolkit for Federation of Terminology Databases—0
Forming Trees with Treeformers—0
Sockeye 3: Fast Neural Machine Translation with PyTorch—0
UM4: Unified Multilingual Multiple Teacher-Student Model for Zero-Resource Neural Machine TranslationCode0
HLT-MT: High-resource Language-specific Training for Multilingual Neural Machine TranslationCode0
A Survey of Task-Based Machine Learning Content Extraction Services for VIDINT—0
A Study of Syntactic Multi-Modality in Non-Autoregressive Machine Translation—0
Part-of-Speech Tagging of Odia Language Using statistical and Deep Learning-Based Approaches—0
End-to-end Speech-to-Punctuated-Text Recognition—0
Vision-and-Language PretrainingCode0
ANEC: An Amharic Named Entity Corpus and Transformer Based Recognizer—0
Non-Autoregressive Neural Machine Translation with Consistency Regularization Optimized Variational Framework—0
Non-Autoregressive Machine Translation: It’s Not as Fast as it Seems—0
Cheat Codes to Quantify Missing Source Information in Neural Machine Translation—0
SURF: Semantic-level Unsupervised Reward Function for Machine Translation—0
Building Multilingual Machine Translation Systems That Serve Arbitrary XY Translations—0
Don’t Take It Literally: An Edit-Invariant Sequence Loss for Text GenerationCode0
Bridging the Gap between Training and Inference: Multi-Candidate Optimization for Diverse Neural Machine TranslationCode0
Raccoons at SemEval-2022 Task 11: Leveraging Concatenated Word Embeddings for Named Entity Recognition—0
Geographical Distance Is The New Hyperparameter: A Case Study Of Finding The Optimal Pre-trained Language For English-isiZulu Machine Translation.—0
Latent Group Dropout for Multilingual and Multidomain Machine Translation—0
Team dina at SemEval-2022 Task 8: Pre-trained Language Models as Baselines for Semantic Similarity—0
Team Innovators at SemEval-2022 for Task 8: Multi-Task Training with Hyperpartisan and Semantic Relation for Multi-Lingual News Article Similarity—0
Reducing Disambiguation Biases in NMT by Leveraging Explicit Word Sense Information—0
Neural Networks in a Product of Hyperbolic Spaces—0
Cross-Language Transfer of High-Quality Annotations: Combining Neural Machine Translation with Cross-Linguistic Span Alignment to Apply NER to Clinical Texts in a Low-Resource LanguageCode0
LSX_team5 at SemEval-2022 Task 8: Multilingual News Article Similarity Assessment based on Word- and Sentence Mover’s Distance—0
Analysing the Correlation between Lexical Ambiguity and Translation Quality in a Multimodal Setting using WordNet—0
Evaluating Gender Bias Transfer from Film Data—0
Improving Neural Machine Translation with the Abstract Meaning Representation by Combining Graph and Sequence TransformersCode0
A Taxonomy of Bias-Causing Ambiguities in Machine Translation—0
HuaAMS at SemEval-2022 Task 8: Combining Translation and Domain Pre-training for Cross-lingual News Article Similarity—0
Uppsala University at SemEval-2022 Task 1: Can Foreign Entries Enhance an English Reverse Dictionary?—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