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.gitattributes

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 # Video files - compressed
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+test.csv filter=lfs diff=lfs merge=lfs -text
+train.csv filter=lfs diff=lfs merge=lfs -text
+validation.csv filter=lfs diff=lfs merge=lfs -text

README.md

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----
-license: mit
----
+---
+license: mit
+task_categories:
+- text-generation
+language:
+- en
+tags:
+- medical
+- biomedical
+- abstract
+- conclusion-generation
+pretty_name: MedConclusion
+size_categories:
+- 1M<n<10M
+---
+
+# MedConclusion
+
+**MedConclusion** is a large-scale dataset of 5.7M PubMed structured abstracts for biomedical conclusion generation. Each instance pairs the non-conclusion sections of an abstract with the original author-written conclusion, providing naturally occurring supervision for evidence-to-conclusion reasoning. MedConclusion also includes journal-level metadata such as biomedical category and SJR, enabling subgroup analysis across biomedical domains.
+
+This repository contains the full version of the dataset.
+
+- **Train**: 70%
+- **Validation**: 10%
+- **Test**: 20%
+
+## Benchmark Information
+
+This dataset is introduced in the paper [MedConclusion: A Benchmark for Biomedical Conclusion Generation from Structured Abstracts](https://arxiv.org/abs/2604.06505).
+
+## Citation
+
+```bibtex
+@article{li2026medconclusion,
+  title={MedConclusion: A Benchmark for Biomedical Conclusion Generation from Structured Abstracts},
+  author={Li, Weiyue and Qian, Ruizhi and Li, Yi and Li, Yongce and Long, Yunfan and Cai, Jiahui and Luo, Yan and Wang, Mengyu},
+  journal={arXiv preprint arXiv:2604.06505},
+  year={2026}
+}
+```

test.csv

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validation.csv

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