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- Over 3.5 Million synthetically generated ground-truth/OCR pairs for post correction tasks from our paper "[Large Synthetic Data from the ar𝜒iv for OCR Post Correction of Historic Scientific Articles](https://dl.acm.org/doi/10.1007/978-3-031-43849-3_23)".
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- ### Citation
 
 
 
 
 
 
 
 
 
 
 
 
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  Please reference the following if you make use of this dataset:
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+ ## Data Introduction
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+ Over 1.5 Million synthetically generated ground-truth/[OCR](https://en.wikipedia.org/wiki/Optical_character_recognition) pairs for post correction tasks from our paper "[Large Synthetic Data from the ar𝜒iv for OCR Post Correction of Historic Scientific Articles](https://dl.acm.org/doi/10.1007/978-3-031-43849-3_23)".
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+ Synthetic ground truth sentences have been mined from the [ar𝜒iv Bulk Downloads](https://info.arxiv.org/help/bulk_data/index.html) source documents,
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+ and Optical Character Recognition (OCR)
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+ sentences have been generated with the [Tesseract](https://github.com/tesseract-ocr/tesseract) OCR engine on the PDF pages generated from compiled source documents.
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+ No page augmentation has been applied to any of the PDF documents (i.e. these are "clean" pages without warping, dust, etc.)
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+ ## Resources
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+ ### Dataset Versions
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+ * V0 (original released with original paper) is available [here](https://zenodo.org/records/8006584)
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+ ## Citation
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  Please reference the following if you make use of this dataset:
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