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README.md

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 license: cc-by-4.0
+language:
+- en
+size_categories:
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+
+# Scientific Openly-Licensed Publications
+This repository contains companion material for the following publication:
+
+> Tim Tarsi, Heike Adel, Jan Hendrik Metzen, Dan Zhang, Matteo Finco, Annemarie Friedrich. **SciOL and MuLMS-Img: Introducing A Large-Scale Multimodal Scientific Dataset and Models for Image-Text Tasks in the Scientific Domain.** WACV 2024.
+
+Please cite this paper if using the dataset, and direct any questions regarding the dataset
+to [Tim Tarsi](mailto:tim.tarsi@gmail.com)
+
+
+## Summary
+Scientific Openly-Licensed Publications (SciOL) is the largest openly-licensed pre-training corpus for multimodal models in the scientific domain, covering multiple sciences including materials science, physics, and computer science. It consists of over 2.7M scientific scientific publications converted into semi-structured data. SciOL contains over 18 Million figure-caption pairs.
+
+**Note: This repository only contains the figures and captions of SciOL. For the textual data see:**  [SciOL-text](https://huggingface.co/datasets/Timbrt/SciOL-text)
+
+## Data Format
+We provide the captions in plain text files and group and compress them together with the images. Each tar file contains 1000 images and captions. We split the data into a train, test and dev set.
+
+
+## Citation
+If you use our dataset in your work, please cite our paper:
+```
+TBD
+
+```
+
+## License
+
+The SciOL corpus is released under the [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) license.