Abstract
Scientific knowledge is predominantly stored in books and scientific journals, often in the form of PDFs. However, the PDF format leads to a loss of semantic information, particularly for mathematical expressions. We propose Nougat (Neural Optical Understanding for Academic Documents), a Visual Transformer model that performs an Optical Character Recognition (OCR) task for processing scientific documents into a markup language, and demonstrate the effectiveness of our model on a new dataset of scientific documents. The proposed approach offers a promising solution to enhance the accessibility of scientific knowledge in the digital age, by bridging the gap between human-readable documents and machine-readable text. We release the models and code to accelerate future work on scientific text recognition.
Community
.
Breakthrough in Document OCR: Meet Nougat - The Neural Transformer for Scientific PDFs!
Links π:
π Subscribe: https://www.youtube.com/@Arxflix
π Twitter: https://x.com/arxflix
π LMNT (Partner): https://lmnt.com/
Models citing this paper 7
Browse 7 models citing this paperDatasets citing this paper 0
No dataset linking this paper