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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 1351–1400 of 10752 papers

TitleStatusHype
How Effective are State Space Models for Machine Translation?Code0
Enhancing Language Learning through Technology: Introducing a New English-Azerbaijani (Arabic Script) Parallel Corpus—0
Automatic Prediction of the Performance of Every Parser—0
NADI 2024: The Fifth Nuanced Arabic Dialect Identification Shared Task—0
Identifying Intensity of the Structure and Content in Tweets and the Discriminative Power of Attributes in Context with Referential Translation Machines—0
Toucan: Many-to-Many Translation for 150 African Language PairsCode0
QET: Enhancing Quantized LLM Parameters and KV cache Compression through Element Substitution and Residual Clustering—0
Finetuning End-to-End Models for Estonian Conversational Spoken Language Translation—0
Evaluating Automatic Metrics with Incremental Machine Translation SystemsCode0
A Case Study on Context-Aware Neural Machine Translation with Multi-Task Learning—0
Regurgitative Training: The Value of Real Data in Training Large Language Models—0
Sentence-level Aggregation of Lexical Metrics Correlates Stronger with Human Judgements than Corpus-level Aggregation—0
How to Learn in a Noisy World? Self-Correcting the Real-World Data Noise on Machine Translation—0
Investigating the potential of Sparse Mixtures-of-Experts for multi-domain neural machine translation—0
Language Portability Strategies for Open-domain Dialogue with Pre-trained Language Models from High to Low Resource Languages—0
ESALE: Enhancing Code-Summary Alignment Learning for Source Code Summarization—0
Towards Massive Multilingual Holistic Bias—0
A Recipe of Parallel Corpora Exploitation for Multilingual Large Language Models—0
Less is More: Accurate Speech Recognition & Translation without Web-Scale Data—0
Voices Unheard: NLP Resources and Models for Yorùbá Regional DialectsCode0
FFN: a Fine-grained Chinese-English Financial Domain Parallel CorpusCode0
A Case Study on Contextual Machine Translation in a Professional Scenario of Subtitling—0
xTower: A Multilingual LLM for Explaining and Correcting Translation Errors—0
Sparse Regression for Machine Translation—0
PrExMe! Large Scale Prompt Exploration of Open Source LLMs for Machine Translation and Summarization EvaluationCode0
Blending LLMs into Cascaded Speech Translation: KIT's Offline Speech Translation System for IWSLT 2024—0
The Progression of Transformers from Language to Vision to MOT: A Literature Review on Multi-Object Tracking with Transformers—0
Shortcomings of LLMs for Low-Resource Translation: Retrieval and Understanding are Both the Problem—0
Enhancing Idiomatic Representation in Multiple Languages via an Adaptive Contrastive Triplet Loss—0
Translating Across Cultures: LLMs for Intralingual Cultural AdaptationCode0
Complexity of Symbolic Representation in Working Memory of Transformer Correlates with the Complexity of a Task—0
xCOMET-lite: Bridging the Gap Between Efficiency and Quality in Learned MT Evaluation MetricsCode0
On the Evaluation Practices in Multilingual NLP: Can Machine Translation Offer an Alternative to Human Translations?—0
MMTE: Corpus and Metrics for Evaluating Machine Translation Quality of Metaphorical Language—0
How effective is Multi-source pivoting for Translation of Low Resource Indian Languages?—0
Lexically Grounded Subword SegmentationCode0
Evaluating Structural Generalization in Neural Machine TranslationCode0
Self-Distillation for Model Stacking Unlocks Cross-Lingual NLU in 200+ Languages—0
AI-Assisted Human Evaluation of Machine TranslationCode0
PFID: Privacy First Inference Delegation Framework for LLMs—0
Does Context Help Mitigate Gender Bias in Neural Machine Translation?—0
Low-Resource Machine Translation through the Lens of Personalized Federated LearningCode0
How Good are LLMs at Relation Extraction under Low-Resource Scenario? Comprehensive EvaluationCode0
LiLiuM: eBay's Large Language Models for e-commerce—0
Unveiling the Power of Source: Source-based Minimum Bayes Risk Decoding for Neural Machine Translation—0
Style Transfer with Multi-iteration Preference OptimizationCode0
CoSTA: Code-Switched Speech Translation using Aligned Speech-Text Interleaving—0
Reconsidering Sentence-Level Sign Language Translation—0
Datasets for Multilingual Answer Sentence Selection—0
Towards Multilingual Audio-Visual Question AnsweringCode0
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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