Update README.md

README.md

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-license: apache-2.0
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+---
+license: apache-2.0
+language:
+- en
+- zh
+---
+# GraphGen-Data
+
+<!-- Provide a quick summary of the dataset. -->
+
+## Data Description
+
+GraphGen-Data is the dataset for verification in the paper "[GraphGen: Enhancing Supervised Fine-Tuning for LLMs with Knowledge-Driven Synthetic Data Generation](https://arxiv.org/abs/2505.20416)".
+It involves three domains:
+- Agricultural(SeedEval)
+- Medical(PQArefEval)
+- General(HotpotEval)
+
+GraphGen is a framework for synthetic data generation guided by knowledge graphs. We released our code in [Github](https://github.com/open-sciencelab/GraphGen).
+
+## Source Data
+
+<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
+
+SeedEval is adapted from [SeedBench](https://arxiv.org/abs/2505.13220), a benchmark with 11 tasks related to seed knowledge. For this study, we selected Task QA–4 (covering one-shot and zero-shot scenarios) related to textual knowledge question answering.
+PQArefEval is derived from [PQAref](https://arxiv.org/abs/2407.05015), from which we extracted 5,818 instances for our analysis.
+[HotpotQA](https://arxiv.org/abs/1809.09600) is a dataset for diverse, explainable multi-hop question answering, where questions require integrating information from multiple sources. We used the test set of HotpotQA as the new evaluation dataset, HotpotEval. 
+Each dataset comprises two components: the QA test set and the corresponding source texts.
+The Corpus for SeedEval is provided by anonymous agricultural experts and cannot be made public due to confidentiality restrictions.
+The Corpus for PQArefEval and HotpotEval are constructed from the original references of PQAref and HotpotQA, respectively. 
+
+## Citation
+
+<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+```
+@misc{chen2025graphgenenhancingsupervisedfinetuning,
+      title={GraphGen: Enhancing Supervised Fine-Tuning for LLMs with Knowledge-Driven Synthetic Data Generation}, 
+      author={Zihong Chen and Wanli Jiang and Jinzhe Li and Zhonghang Yuan and Huanjun Kong and Wanli Ouyang and Nanqing Dong},
+      year={2025},
+      eprint={2505.20416},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2505.20416}, 
+}
+```