Fighting Fire with Fire: Can ChatGPT Detect AI-generated Text?
Bhattacharjee, Amrita, Liu, Huan
–arXiv.org Artificial Intelligence
Large language models (LLMs) such as ChatGPT are increasingly being used for various use cases, including text content generation at scale. Although detection methods for such AI-generated text exist already, we investigate ChatGPT's performance as a detector on such AI-generated text, inspired by works that use ChatGPT as a data labeler or annotator. We evaluate the zeroshot performance of ChatGPT in the task of human-written vs. AI-generated text detection, and perform experiments on publicly available datasets. We empirically investigate if ChatGPT is symmetrically effective in detecting AI-generated or human-written text. Our findings provide insight on how ChatGPT and similar LLMs may be leveraged in automated detection pipelines by simply focusing on solving a specific aspect of the problem and deriving Figure 1: We use OpenAI's ChatGPT as a detector to distinguish the rest from that solution. All code and data is available at between human-written and AI-generated text.
arXiv.org Artificial Intelligence
Aug-17-2023
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- Research Report > New Finding (0.66)
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- Media (0.46)
- Government > Regional Government (0.46)
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