task_categories:text-classification size_categories:100M<n<1B language:en license:apache-2.0 arxiv:2310.01307 region:us
---
license: apache-2.0
task_categories:
- text-classification
language:
- en
size_categories:
- 100M<n<1B
---

# Dataset Card for HC-Var (Human and ChatGPT Texts with Variety)

This is a collection of human texts and ChatGPT (GPT3.5-Turbo) generated texts, to faciliate studies such as generated texts detection. 
It includes the texts which are generated / human written to accomplish various language tasks with various approaches. 
The included language tasks and topics are summarized below. Note: For each language task, this dataset considers 3 different prompts to inquire ChatGPT outputs.
The example code to train binary classification models is in [this website](https://github.com/hannxu123/hc_var). 
A technical report on some representative detection methods can be find in [this paper](https://arxiv.org/abs/2310.01307).
This dataset is collected by Han Xu from Michigan State
University. Potential issues and suggestions are welcomed to be dicussed in the community panel or emails to xuhan1@msu.edu. 

## Key variables in the dataset: 
**text**: The text body (including either human or ChatGPT texts.)\
**domain**: The language tasks included in this dataset: News, Review, (Essay) Writing, QA\
**topic**: The topic in each task.\
**prompt**: The prompt used to obtain ChatGPT outputs. "N/A" for human texts.\
**pp_id**: Each task has 3 prompts to inquire ChatGPT outputs. The "pp_id" denotes the index of prompt. "0" for human texts. "1-3" for ChatGPT texts.\
**label**: "0" for human texts. "1" for ChatGPT texts.

## To cite this dataset
```
@misc{xu2023generalization,
      title={On the Generalization of Training-based ChatGPT Detection Methods}, 
      author={Han Xu and Jie Ren and Pengfei He and Shenglai Zeng and Yingqian Cui and Amy Liu and Hui Liu and Jiliang Tang},
      year={2023},
      eprint={2310.01307},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
```
