Datasets › Vis-CheBI20
Vis-CheBI20
Molecules represent tokens of the language of chemistry, which underlies not only chemistry itself, but also scientific fields that use chemical information such as pharmacy, material science, and molecular biology. Existing molecular information is distributed across text books, publications, and patents. To describe structural information (spatial arrangement of atoms), molecules are commonly drawn as 2D images in such documents, which makes Optical Chemical Structure Understanding (OCSU) play an important role in molecule-centric scientific discovery.
OCSU aims to automatically translate chemical structure diagrams into chemist-readable or machine-readable strings that describe the molecule from motif level to molecule level and abstract level. Typically, it includes four subtasks, that is, functional group caption, molecular description, chemist-readable IUPAC naming, and machine-readable SMILES naming (OCSR). On the basis of these, molecular structural information can be fully extracted to support downstream tasks, such as moleculecentric chat, property prediction, and molecule editing.
Vis-CheBI20 is released for Optical Chemical Structure Understanding (OCSU) task, built on the basis of CheBI-20 molecule description dataset.
Benchmarks archive 2025-07-28
No leaderboard in the archive resolves to this dataset.
Papers archive 2025-07-28
No paper in the archive has a leaderboard row on this dataset; the archive counts 1 paper for it but never published that list.
Dataset loaders archive 2025-07-28
No loader listed in the archive.
Tasks archive 2025-07-28
No task tagged in the archive.
License archive 2025-07-28
No licence recorded in the archive. Absence here is not a statement about the dataset's terms.
Modalities archive 2025-07-28
Languages archive 2025-07-28
No language tagged.
Variants archive 2025-07-28
- Vis-CheBI20
1 variant name, as the archive lists them.
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