使用机器学习区分人类生成文本与 ChatGPT 生成文本
Distinguishing Human Generated Text From ChatGPT Generated Text Using Machine Learning
AI总结：
本文提出基于机器学习的 ChatGPT 生成文本检测方法，在含 10,000 条文本的 Kaggle 数据集上比较 11 种算法，并在 GPT-3.5 语料上达到 77% 准确率。
摘要：
ChatGPT 是一种对话式人工智能，属于大型语言模型家族中的生成式预训练 Transformer 成员。该文本生成模型通过监督学习和强化学习进行了微调，因此能够生成看似由自然智能撰写的文本文档。尽管这一生成模型具有众多优势，但它也带来了一些合理的担忧。本文提出了一种基于机器学习的解决方案，能够从人类撰写的文本中识别 ChatGPT 提供的文本，同时对分类过程中总共 11 种机器学习和深度学习算法进行了比较分析。我们在一个包含 10,000 条文本的 Kaggle 数据集上测试了所提出的模型，其中 5,204 条文本由人类撰写，并收集自新闻和社交媒体。在由 GPT-3.5 生成的语料库上，所提出算法达到了 77% 的准确率。
英文摘要：
ChatGPT is a conversational artificial intelligence that is a member of the generative pre-trained transformer of the large language model family. This text generative model was fine-tuned by both supervised learning and reinforcement learning so that it can produce text documents that seem to be written by natural intelligence. Although there are numerous advantages of this generative model, it comes with some reasonable concerns as well. This paper presents a machine learning-based solution that can identify the ChatGPT delivered text from the human written text along with the comparative analysis of a total of 11 machine learning and deep learning algorithms in the classification process. We have tested the proposed model on a Kaggle dataset consisting of 10,000 texts out of which 5,204 texts were written by humans and collected from news and social media. On the corpus generated by GPT-3.5, the proposed algorithm presents an accuracy of 77%.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
