title: Nougat: Neural Optical Understanding for Academic Documents
summary: 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.
paper_authors._id: 64ec766ac782d648d293ebbf
paper_authors.name: Lukas Blecher
paper_authors.status: extracted_pending
paper_authors.statusLastChangedAt: 2023-08-28T10:26:51.380Z
paper_authors._id: 628d313986d23ad156081735
paper_authors.avatarUrl: /avatars/64f52fab209d478aaf0be7b64e13be37.svg
paper_authors.fullname: Lukas Blecher
paper_authors.type: user
paper_authors.user: lukbl
paper_authors._id: 64ec766ac782d648d293ebc0
paper_authors.name: Guillem Cucurull
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2024-04-26T09:03:51.651Z
paper_authors._id: 64b9069c8815d865211e280c
paper_authors.avatarUrl: /avatars/1da1d77db9684960dbf27460b7d50739.svg
paper_authors.fullname: Guillem
paper_authors.type: user
paper_authors.user: gcucurull
paper_authors._id: 64ec766ac782d648d293ebc1
paper_authors.name: Thomas Scialom
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2023-08-28T12:24:36.291Z
paper_authors._id: 60c0e0c06c0791283058f0fb
paper_authors.avatarUrl: /avatars/84c0fe390a171e68b79a8274405ebf06.svg
paper_authors.fullname: Scialom
paper_authors.type: user
paper_authors.user: ThomasNLG
paper_authors._id: 64ec766ac782d648d293ebc2
paper_authors.name: Robert Stojnic
paper_title: Nougat: Neural Optical Understanding for Academic Documents
paper_summary: 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.
paper_ai_keywords: Visual Transformer Optical Character Recognition (OCR) markup language