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 8401–8450 of 10752 papers

TitleStatusHype
MultiGranCNN: An Architecture for General Matching of Text Chunks on Multiple Levels of Granularity—0
Multi-Granularity Self-Attention for Neural Machine Translation—0
Multi-Head Highly Parallelized LSTM Decoder for Neural Machine Translation—0
Multi-Hop Transformer for Document-Level Machine Translation—0
Multi-Hypothesis Machine Translation Evaluation—0
Multi-Layer Softmaxing during Training Neural Machine Translation for Flexible Decoding with Fewer Layers—0
Multi-level Evaluation for Machine Translation—0
Multi-level Translation Quality Prediction with QuEst++—0
Multilingual Agreement for Multilingual Neural Machine Translation—0
Multilingual Aliasing for Auto-Generating Proposition Banks—0
Multilingual and Cross-Lingual Intent Detection from Spoken Data—0
Multilingual Argument Mining: Datasets and Analysis—0
Multilingual CheckList: Generation and Evaluation—0
Multilingual Contextualization of Large Language Models for Document-Level Machine Translation—0
Multilingual Dictionary Based Construction of Core Vocabulary—0
Multilingual Disfluency Removal using NMT—0
Multilingual Document-Level Translation Enables Zero-Shot Transfer From Sentences to Documents—0
Multilingual Document-Level Translation Enables Zero-Shot Transfer From Sentences to Documents—0
Multilingual Domain Adaptation for NMT: Decoupling Language and Domain Information with Adapters—0
Multilingual Domain Adaptation for NMT: Decoupling Language and Domain Information with Adapters—0
Multilingual End-to-End Speech Translation—0
Multi-lingual Entity Discovery and Linking—0
Multilingual Evaluation of Semantic Textual Relatedness—0
Multilingual eXtended WordNet Knowledge Base: Semantic Parsing and Translation of Glosses—0
Multi-lingual Geoparsing based on Machine Translation—0
Multilingual Large Language Models Are Not (Yet) Code-Switchers—0
Multilingual Machine Translation: Closing the Gap between Shared and Language-specific Encoder-Decoders—0
Multilingual Machine Translation Evaluation Metrics Fine-tuned on Pseudo-Negative Examples for WMT 2021 Metrics Task—0
Multilingual Machine Translation Systems at WAT 2021: One-to-Many and Many-to-One Transformer based NMT—0
Multilingual Machine Translation Systems from Microsoft for WMT21 Shared Task—0
Multilingual Machine Translation with Open Large Language Models at Practical Scale: An Empirical Study—0
Multilingual Machine Translation with Quantum Encoder Decoder Attention-based Convolutional Variational Circuits—0
Multilingual Mix: Example Interpolation Improves Multilingual Neural Machine Translation—0
Multilingual Multi-Domain Adaptation Approaches for Neural Machine Translation—0
Multilingual Multi-Domain NMT for Indian Languages—0
Multilingual Multi-modal Embeddings for Natural Language Processing—0
Multilingual Multimodal Language Processing Using Neural Networks—0
Multilingual Multimodal Machine Translation for Dravidian Languages utilizing Phonetic Transcription—0
Multilingual, Multi-scale and Multi-layer Visualization of Intermediate Representations—0
Multilingual Neural Machine Translation involving Indian Languages—0
Multilingual Neural Machine Translation—0
Multilingual Neural Machine Translation System for Indic to Indic Languages—0
Multilingual Neural Machine Translation:Can Linguistic Hierarchies Help?—0
Multilingual Neural Machine Translation: Can Linguistic Hierarchies Help?—0
Multilingual Neural Machine Translation: Case-study for Catalan, Spanish and Portuguese Romance Languages—0
Multilingual Neural Machine Translation with Task-Specific Attention—0
Multilingual Neural Machine Translation With the Right Amount of Sharing—0
Multilingual Neural Machine Translation with Deep Encoder and Multiple Shallow Decoders—0
Multilingual Neural Machine Translation with Language Clustering—0
Multilingual Parallel Corpus for Global Communication Plan—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