Update README.md

README.md

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-license: cc-by-nc-4.0
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+---
+license: cc-by-nc-4.0
+---
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+<p align="center">
+  <img src="figs/favicon.svg" width="150">
+</p>
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+<div align="center">
+  <h1>Evaluating Text Creativity across Diverse Domains: A Dataset and a Large Language Model Evaluator</h1>
+  <a href="https://creval-creative-evaluation.github.io/"><img src="https://img.shields.io/badge/Project%20Page-666?logo=googledocs&logoColor=FFE165&style=for-the-badge" alt="homepage"></a>
+  <a href="https://arxiv.org/pdf/2505.19236"><img src="https://img.shields.io/badge/arXiv%20paper-666?logo=arxiv&logoColor=FFE165&style=for-the-badge" alt="arXiv"></a>
+  <br/>
+  <a href="https://huggingface.co/datasets/Aman/CreataSet"><img src="https://img.shields.io/badge/CreataSet-dataset-blue?logo=databricks&logoColor=white&style=for-the-badge" alt="arXiv"></a>
+  <a href="https://huggingface.co/Aman/CrEval-7b"><img src="https://img.shields.io/badge/model-7b-purple?logo=huggingface&logoColor=yellow&style=for-the-badge" alt="arXiv"></a>
+  <a href="https://huggingface.co/Aman/CrEval-14b"><img src="https://img.shields.io/badge/model-14b-purple?logo=huggingface&logoColor=yellow&style=for-the-badge" alt="arXiv"></a>
+  <a href="https://github.com/Aman-4-Real/CrEval"><img src="https://img.shields.io/badge/github-code-black?logo=github&logoColor=white&style=for-the-badge" alt="arXiv"></a>
+  <br/>
+  <hr>
+</div>
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+We introduce **CreataSet**, a large-scale dataset of over **1M** creative instruction-response pairs across **87** domains. This dataset can facilitate the meta-evaluation of pairwise comparison models for assessing text creativity. Also, this dataset can be used for training creative generation models. More details please refer to our [paper](https://arxiv.org/abs/2505.19236).
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+
+<p align="center">
+  <img src="figs/teaser.png" width="1000">
+  Figure 1. An example of how to formulate the problem of text creativity evaluation to better evaluate.
+</p>
+
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+**License**: This dataset is made available under the `cc-by-nc-4.0` License. In addition, we respect and uphold the usage terms of the original data providers. If you believe that any part of this dataset affects your legal rights or raises other concerns, please reach out to us. We will carefully review your request and respond without delay.
+
+
+```
+@article{cao2025evaluating,
+  title={Evaluating Text Creativity across Diverse Domains: A Dataset and Large Language Model Evaluator},
+  author={Cao, Qian and Wang, Xiting and Yuan, Yuzhuo and Liu, Yahui and Luo, Fang and Song, Ruihua},
+  journal={arXiv preprint arXiv:2505.19236},
+  year={2025}
+}
+```
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