Shulou(Shulou.com)11/24 Report--

CTOnews.com, January 29, the use of large language models (LLM) is surging, especially since ChatGPT has been so popular recently that it is so powerful that it can even generate papers for students. Because of this, there is a need for a system to detect machine-generated text.

Recently, a research team at Stanford University proposed a new approach called DetectGPT, which aims to be one of the first tools to combat machine-generated text in higher education. This method is based on the principle that the text generated by LLM usually hovers in a specific region of the negative curvature region of the logarithmic probability function of the model. With this discovery, the team developed a new indicator to determine whether the text was machine-generated and did not need to train artificial intelligence or collect large data sets to compare texts.

This method, known as "zero-shot", allows DetectGPT to detect machine-written text without knowing what artificial intelligence tools are used to generate text. Its operation is in sharp contrast to other methods that need to train "classifiers" and real and generate paragraph data sets.

CTOnews.com learned that the team tested DetectGPT on a dataset of fake news articles, and it outperformed other zero-time learning methods in detecting machine-generated text. The team claims a substantial improvement in detection performance and suggests that DetectGPT may be a promising way to carefully examine machine-generated text.

In short, DetectGPT is a new method for detecting machine-generated text, which takes advantage of the unique characteristics of LLM-generated text. It is a zero-time learning method that does not require any additional data or training, making it an efficient and effective tool for identifying machine-generated text. As the use of LLM continues to grow, the importance of the corresponding system for detecting machine-generated text will become more and more critical. DetectGPT is a promising method that can have a significant impact in many areas, and its further development may be beneficial to many areas.

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