mlsanityData to 7 Oct 2026

Tagged Back-Translation

arXiv 1906.06442 ↗First posted 15 Jun 2019cs.CL cs.LGcited by 76

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Abstract (arXiv)

Recent work in Neural Machine Translation (NMT) has shown significant quality gains from noised-beam decoding during back-translation, a method to generate synthetic parallel data. We show that the main role of such synthetic noise is not to diversify the source side, as previously suggested, but simply to indicate to the model that the given source is synthetic. We propose a simpler alternative to noising techniques, consisting of tagging back-translated source sentences with an extra token. Our results on WMT outperform noised back-translation in English-Romanian and match performance on English-German, re-defining state-of-the-art in the former.

Key facts. Cited by 76 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Jun 2019.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 26; 2022: 16; 2023: 14; 2024: 12; 2025: 5; 2026: 3.

76 papers.

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  1. 2022PaLM: Scaling Language Modeling with Pathwayscited by 5,304
  2. 2023Prompting Large Language Model for Machine Translation: A Case Studycited by 247
  3. 2023Self-Alignment with Instruction Backtranslationcited by 149
  4. 2021Neural Machine Translation for Low-Resource Languages: A Surveycited by 108
  5. 2024Best Practices and Lessons Learned on Synthetic Datacited by 104
  6. 2021Survey of Low-Resource Machine Translationcited by 92
  7. 2021Synthetic Data Generation for Grammatical Error Correction with Tagged Corruption Modelscited by 56
  8. 2021Domain Adaptation and Multi-Domain Adaptation for Neural Machine Translation: A Surveycited by 46
  9. 2021Why don't people use character-level machine translation?cited by 27
  10. 2022Using natural language prompts for machine translationcited by 27
  11. 2021Isometric MT: Neural Machine Translation for Automatic Dubbingcited by 18
  12. 2023DUB: Discrete Unit Back-translation for Speech Translationcited by 18
38 more
  1. 2025Enhancing LLM Safety Through a Theoretical Minimax Game Lenscited by 18
  2. 2021Rethinking Perturbations in Encoder-Decoders for Fast Trainingcited by 17
  3. 2021Self-Training Sampling with Monolingual Data Uncertainty for Neural Machine Translationcited by 17
  4. 2021Improving Neural Machine Translation by Bidirectional Trainingcited by 17
  5. 2021A Survey on Low-Resource Neural Machine Translationcited by 16
  6. 2021On the Complementarity between Pre-Training and Back-Translation for Neural Machine Translationcited by 14
  7. 2022Understanding Translationese in Cross-Lingual Summarizationcited by 14
  8. 2022Tencent's Multilingual Machine Translation System for WMT22 Large-Scale African Languagescited by 13
  9. 2021On the Language Coverage Bias for Neural Machine Translationcited by 12
  10. 2021Self-supervised and Supervised Joint Training for Resource-rich Machine Translationcited by 12
  11. 2022Domain-Specific Text Generation for Machine Translationcited by 12
  12. 2021The USYD-JD Speech Translation System for IWSLT 2021cited by 11
  13. 2021WeChat Neural Machine Translation Systems for WMT21cited by 11
  14. 2021Hierarchical Neural Data Synthesis for Semantic Parsingcited by 11
  15. 2022Non-Autoregressive Machine Translation: It's Not as Fast as it Seemscited by 11
  16. 2021Comparison of Grammatical Error Correction Using Back-Translation Modelscited by 9
  17. 2023Back Translation for Speech-to-text Translation Without Transcriptscited by 9
  18. 2023Quality-Aware Translation Models: Efficient Generation and Quality Estimation in a Single Modelcited by 9
  19. 2021Multi-Domain Adaptation in Neural Machine Translation Through Multidimensional Taggingcited by 8
  20. 2021Rethinking Data Augmentation for Low-Resource Neural Machine Translation: A Multi-Task Learning Approachcited by 8
  21. 2022ExtraPhrase: Efficient Data Augmentation for Abstractive Summarizationcited by 8
  22. 2024Scaling Sign Language Translationcited by 8
  23. 2023Bilex Rx: Lexical Data Augmentation for Massively Multilingual Machine Translationcited by 7
  24. 2023Neural Machine Translation for the Indigenous Languages of the Americas: An Introductioncited by 7
  25. 2023Tagged End-to-End Simultaneous Speech Translation Training using Simultaneous Interpretation Datacited by 6
  26. 2022Cyberbullying Classifiers are Sensitive to Model-Agnostic Perturbationscited by 5
  27. 2022Geographical Distance Is The New Hyperparameter: A Case Study Of Finding The Optimal Pre-trained Language For English-isiZulu Machine Translationcited by 5
  28. 2022Exploring Diversity in Back Translation for Low-Resource Machine Translationcited by 5
  29. 2023Translating away Translationese without Parallel Datacited by 5
  30. 2024Rule-Based, Neural and LLM Back-Translation: Comparative Insights from a Variant of Ladincited by 5
  31. 2021AUGVIC: Exploiting BiText Vicinity for Low-Resource NMTcited by 4
  32. 2021On Systematic Style Differences between Unsupervised and Supervised MT and an Application for High-Resource Machine Translationcited by 4
  33. 2022Improving Neural Machine Translation by Denoising Trainingcited by 4
  34. 2023On Synthetic Data for Back Translationcited by 4
  35. 2024Choose the Final Translation from NMT and LLM hypotheses Using MBR Decoding: HW-TSC's Submission to the WMT24 General MT Shared Taskcited by 4
  36. 2021The Volctrans Neural Speech Translation System for IWSLT 2021cited by 3
  37. 2021Alternated Training with Synthetic and Authentic Data for Neural Machine Translationcited by 3
  38. 2021HintedBT: Augmenting Back-Translation with Quality and Transliteration Hintscited by 3

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