---
title: README
emoji: 🏆
colorFrom: green
colorTo: pink
sdk: static
pinned: false
---

We are dedicated to LLMs that serve the agricultural sector. Specifically, due to the current lack of fine-tuning datasets for LLMs in crop science, 
we have released our CROP dataset, which is a large open-source dataset with over 210K Q&A pairs. Furthermore, to provide a high-quality evaluation standard for this vertical domain, 
we have introduced the CROP benchmark, which is a large open-source dataset with 5045 multiple-choice questions. 
We hope our work will advance the field of LLMs in agricultural production and contribute to solving hunger issues.

## Note
**Our work is accepted by NeurIPS2024 Dataset & Benchmark Track.**
All datasets and benchmarks are open-sourced. You can see our project website at **https://github.com/RenqiChen/The_Crop** for more details about our work. 

## BibTeX & Citation

If you find our codes and datasets useful, please consider citing our work:

```bibtex
@inproceedings{zhangempowering,
  title={Empowering and Assessing the Utility of Large Language Models in Crop Science},
  author={Zhang, Hang and Sun, Jiawei and Chen, Renqi and Liu, Wei and Yuan, Zhonghang and Zheng, Xinzhe and Wang, Zhefan and Yang, Zhiyuan and Yan, Hang and Zhong, Han-Sen and others},
  booktitle={The Thirty-eight Conference on Neural Information Processing Systems Datasets and Benchmarks Track}
}
```