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--- |
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language: |
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- en |
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thumbnail: url to a thumbnail used in social sharing |
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tags: |
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- ArguGPT |
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license: mit |
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datasets: |
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- SJTU-CL/ArguGPT |
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metrics: |
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- accuracy |
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pipeline_tag: text-classification |
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--- |
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# ArguGPT |
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RoBERTa-large finetuned on ArguGPT essays. |
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- label 1 for machine generated essays |
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- label 0 for human written essays |
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**Please truncate your input essay to 512 tokens** |
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## Citation |
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Please cite our work [arXiv:2304.07666](https://arxiv.org/abs/2304.07666) as |
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``` |
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@misc{liu2023argugpt, |
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title={ArguGPT: evaluating, understanding and identifying argumentative essays generated by GPT models}, |
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author={Yikang Liu and Ziyin Zhang and Wanyang Zhang and Shisen Yue and Xiaojing Zhao and Xinyuan Cheng and Yiwen Zhang and Hai Hu}, |
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year={2023}, |
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eprint={2304.07666}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL} |
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} |
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``` |
