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 1451–1500 of 10752 papers

TitleStatusHype
LLM-Assisted Rule Based Machine Translation for Low/No-Resource Languages—0
CANTONMT: Investigating Back-Translation and Model-Switch Mechanisms for Cantonese-English Neural Machine TranslationCode0
An Empirical Study on the Robustness of Massively Multilingual Neural Machine TranslationCode0
Learning to Solve Geometry Problems via Simulating Human Dual-Reasoning ProcessCode0
Using Machine Translation to Augment Multilingual Classification—0
Fine-tuning Pre-trained Named Entity Recognition Models For Indian Languages—0
Automated Program Repair: Emerging trends pose and expose problems for benchmarks—0
Kreyòl-MT: Building MT for Latin American, Caribbean and Colonial African Creole LanguagesCode0
Guylingo: The Republic of Guyana Creole CorporaCode0
Relay Decoding: Concatenating Large Language Models for Machine Translation—0
Comparative study of models trained on synthetic data for Ukrainian grammatical error correctionCode0
Sentiment Analysis Across Languages: Evaluation Before and After Machine Translation to EnglishCode0
The Call for Socially Aware Language Technologies—0
The IgboAPI Dataset: Empowering Igbo Language Technologies through Multi-dialectal Enrichment—0
Reinforcement Learning for Edit-Based Non-Autoregressive Neural Machine Translation—0
Efficient Sample-Specific Encoder Perturbations—0
Suvach -- Generated Hindi QA benchmark—0
Does Generative AI speak Nigerian-Pidgin?: Issues about Representativeness and Bias for Multilingualism in LLMsCode0
Context-Aware Machine Translation with Source Coreference ExplanationCode0
Modeling Orthographic Variation Improves NLP Performance for Nigerian Pidgin—0
Quality Estimation with k-nearest Neighbors and Automatic Evaluation for Model-specific Quality Estimation—0
I Have an Attention Bridge to Sell You: Generalization Capabilities of Modular Translation Architectures—0
Scaffold-BPE: Enhancing Byte Pair Encoding for Large Language Models with Simple and Effective Scaffold Token Removal—0
Usefulness of Emotional Prosody in Neural Machine Translation—0
TIGQA:An Expert Annotated Question Answering Dataset in Tigrinya—0
Prefix Text as a Yarn: Eliciting Non-English Alignment in Foundation Language Model—0
Translation of Multifaceted Data without Re-Training of Machine Translation Systems—0
BERT vs GPT for financial engineering—0
Neural Proto-Language Reconstruction—0
Automated Multi-Language to English Machine Translation Using Generative Pre-Trained Transformers—0
Sentence-Level or Token-Level? A Comprehensive Study on Knowledge Distillation—0
Fine-Tuning Large Language Models to Translate: Will a Touch of Noisy Data in Misaligned Languages Suffice?—0
From LLM to NMT: Advancing Low-Resource Machine Translation with Claude—0
Evaluation of Machine Translation Based on Semantic Dependencies and Keywords—0
Enhancing Length Extrapolation in Sequential Models with Pointer-Augmented Neural Memory—0
Simultaneous Interpretation Corpus Construction by Large Language Models in Distant Language PairCode0
NLP-enabled Trajectory Map-matching in Urban Road Networks using a Transformer-based Encoder-decoder—0
Neuron Specialization: Leveraging intrinsic task modularity for multilingual machine translation—0
GeMQuAD : Generating Multilingual Question Answering Datasets from Large Language Models using Few Shot Learning—0
Multilingual Evaluation of Semantic Textual Relatedness—0
Investigating Neural Machine Translation for Low-Resource Languages: Using Bavarian as a Case StudyCode0
Extending Translate-Train for ColBERT-X to African Language CLIR—0
Curated Datasets and Neural Models for Machine Translation of Informal Registers between Mayan and Spanish VernacularsCode0
Introducing L2M3, A Multilingual Medical Large Language Model to Advance Health Equity in Low-Resource Regions—0
Control-DAG: Constrained Decoding for Non-Autoregressive Directed Acyclic T5 using Weighted Finite State AutomataCode0
An inclusive review on deep learning techniques and their scope in handwriting recognition—0
Charles Translator: A Machine Translation System between Ukrainian and Czech—0
Interplay of Machine Translation, Diacritics, and Diacritization—0
Exploring the Necessity of Visual Modality in Multimodal Machine Translation using Authentic Datasets—0
Semantic Stealth: Adversarial Text Attacks on NLP Using Several Methods—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