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 6751–6800 of 10752 papers

TitleStatusHype
Rule-Based Translation of Spanish Verb-Noun Combinations into Basque—0
Rule Based Transliteration Scheme for English to Punjabi—0
Rule Extraction for Tree-to-Tree Transducers by Cost Minimization—0
Rule Selection with Soft Syntactic Features for String-to-Tree Statistical Machine Translation—0
Russian-Chinese Sentence-level Aligned News Corpus—0
Russian-English Bidirectional Machine Translation System—0
Russian Stress Prediction using Maximum Entropy Ranking—0
RWTH-PHOENIX-Weather: A Large Vocabulary Sign Language Recognition and Translation Corpus—0
S2SPMN: A Simple and Effective Framework for Response Generation with Relevant Information—0
SAARSHEFF at SemEval-2016 Task 1: Semantic Textual Similarity with Machine Translation Evaluation Metrics and (eXtreme) Boosted Tree Ensembles—0
SAC: Accelerating and Structuring Self-Attention via Sparse Adaptive Connection—0
Sadeed: Advancing Arabic Diacritization Through Small Language Model—0
SAGAN: A Machine Translation Approach for Cross-Lingual Textual Entailment—0
SAGAN: An approach to Semantic Textual Similarity based on Textual Entailment—0
SAHAAYAK 2023 -- the Multi Domain Bilingual Parallel Corpus of Sanskrit to Hindi for Machine Translation—0
SAHSOH@QALB-2015 Shared Task: A Rule-Based Correction Method of Common Arabic Native and Non-Native Speakers' Errors—0
Salience Estimation with Multi-Attention Learning for Abstractive Text Summarization—0
SALTED: A Framework for SAlient Long-Tail Translation Error Detection—0
Same domain different discourse style - A case study on Language Resources for data-driven Machine Translation—0
Same evaluation, more tokens: On the effect of input length for machine translation evaluation using Large Language Models—0
Same-language machine translation for local flavours/flavors—0
SAMER: A Semi-Automatically Created Lexical Resource for Arabic Verbal Multiword Expressions Tokens Paradigm and their Morphosyntactic Features—0
Sampling-based Alignment and Hierarchical Sub-sentential Alignment in Chinese--Japanese Translation of Patents—0
Sampling Tree Fragments from Forests—0
Samsung: Align-and-Differentiate Approach to Semantic Textual Similarity—0
Samsung Poland NLP Team at SemEval-2016 Task 1: Necessity for diversity; combining recursive autoencoders, WordNet and ensemble methods to measure semantic similarity.—0
SANA: A Large Scale Multi-Genre, Multi-Dialect Lexicon for Arabic Subjectivity and Sentiment Analysis—0
SANVis: Visual Analytics for Understanding Self-Attention Networks—0
SARAL: A Low-Resource Cross-Lingual Domain-Focused Information Retrieval System for Effective Rapid Document Triage—0
Saving RNN Computations with a Neuron-Level Fuzzy Memoization Scheme—0
SBAT: Video Captioning with Sparse Boundary-Aware Transformer—0
Scaffold-BPE: Enhancing Byte Pair Encoding for Large Language Models with Simple and Effective Scaffold Token Removal—0
Scalable and Efficient MoE Training for Multitask Multilingual Models—0
Scalable Cross Lingual Pivots to Model Pronoun Gender for Translation—0
Scalable Decipherment for Machine Translation via Hash Sampling—0
Scalable Large-Margin Structured Learning: Theory and Algorithms—0
Scalable Modified Kneser-Ney Language Model Estimation—0
Scalable Multilingual Frontend for TTS—0
Scalable Transformers for Neural Machine Translation—0
Scaling Laws for Downstream Task Performance of Large Language Models—0
Scaling Laws for Multilingual Neural Machine Translation—0
Scaling Laws for Neural Machine Translation—0
Scaling Laws of Decoder-Only Models on the Multilingual Machine Translation Task—0
Scaling Low-Resource MT via Synthetic Data Generation with LLMs—0
Scaling Memory-Augmented Neural Networks with Sparse Reads and Writes—0
Scaling Recurrent Neural Network Language Models—0
Scaling Semantic Frame Annotation—0
Scaling Sign Language Translation—0
Scaling Up Word Clustering—0
scb-mt-en-th-2020: A Large English-Thai Parallel Corpus—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