Add minimal dataset card

README.md

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-license: cc-by-nc-sa-4.0
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+---
+license: cc-by-nc-sa-4.0
+language:
+- en
+pretty_name: 'ParaRev: Scientific Paragraph Revision Dataset'
+size_categories:
+- 10K<n<100K
+---
+
+# ParaRev: Scientific Paragraph Revision Dataset
+
+> Revision is a crucial step in scientific writing, where authors refine their work to improve clarity, structure, and academic quality. Existing approaches to automated writing assistance often focus on sentence-level revisions, which fail to capture the broader context needed for effective modification. In this paper, we explore the impact of shifting from sentence-level to paragraph-level scope for the task of scientific text revision. The paragraph level definition of the task allows for more meaningful changes, and is guided by detailed revision instructions rather than general ones. To support this task, we introduce ParaRev, the first dataset of revised scientific paragraphs with an evaluation subset manually annotated with revision instructions. Our experiments demonstrate that using detailed instructions significantly improves the quality of automated revisions compared to general approaches, no matter the model or the metric considered. [Source](https://huggingface.co/papers/2501.05222)
+
+The ParaRev dataset contains pairs of original and revised paragraphs from scientific papers, annotated with revision instructions and labels. It is designed to support research in scientific writing assistance, specifically focused on paragraph-level revisions. 
+
+## Dataset Summary
+
+- **Size**: 48,203 paragraph pairs total, with 641 manually annotated pairs
+- **Source**: Extracted from the CASIMIR corpus of scientific papers
+- **Task**: Paragraph-level text revision
+- **Languages**: English
+
+## Citation
+
+```bibtex
+@inproceedings{jourdan2024pararev,
+    title={ParaRev: Building a dataset for Scientific Paragraph Revision annotated with revision instruction},
+    author={Jourdan, Léane and Hernandez, Nicolas and Dufour, Richard and Boudin, Florian and Aizawa, Akiko},
+    booktitle={Proceedings of LREC-COLING 2024},
+    year={2024}
+}