mlsanityData to 7 Oct 2026

Neural Machine Translation: A Review and Survey

arXiv 1912.02047 ↗First posted 4 Dec 2019cs.CLcited by 99

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Abstract (arXiv)

The field of machine translation (MT), the automatic translation of written text from one natural language into another, has experienced a major paradigm shift in recent years. Statistical MT, which mainly relies on various count-based models and which used to dominate MT research for decades, has largely been superseded by neural machine translation (NMT), which tackles translation with a single neural network. In this work we will trace back the origins of modern NMT architectures to word and sentence embeddings and earlier examples of the encoder-decoder network family. We will conclude with a survey of recent trends in the field.

Key facts. Cited by 99 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Dec 2019.

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Citing papers per year: 2021: 10; 2022: 11; 2023: 30; 2024: 25; 2025: 12; 2026: 11.

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  10. 2023From task structures to world models: What do LLMs know?cited by 46
  11. 2023Watermarking Conditional Text Generation for AI Detection: Unveiling Challenges and a Semantic-Aware Watermark Remedycited by 45
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38 more
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  5. 2021Symbolic Behaviour in Artificial Intelligencecited by 24
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  7. 2022A Dataset for Plain Language Adaptation of Biomedical Abstractscited by 19
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  9. 2021Rethinking Neural Operations for Diverse Taskscited by 18
  10. 2025Multilingual Language Model Pretraining using Machine-translated Datacited by 17
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  15. 2022A Survey on Backdoor Attack and Defense in Natural Language Processingcited by 13
  16. 2022Toward automatic generation of control structures for process flow diagrams with large language modelscited by 12
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  18. 2024Prompt Refinement with Image Pivot for Text-to-Image Generationcited by 11
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  38. 2021PENELOPIE: Enabling Open Information Extraction for the Greek Language through Machine Translationcited by 3

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