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What is AI vs Human Text Detection Using DRNN about?

This paper presents a study on distinguishing between AI-generated and human-written text using modified Deep Recurrent Neural Networks (DRNN). Two architectures, DRNN-1 and DRNN-2, were developed and tested on a dataset of 900 answers from students and ChatGPT, achieving a test accuracy of 88.52% with the combined dataset. The research highlights the importance of classifying text for authenticity, trust, and regulatory purposes as AI-generated content becomes more prevalent.

Author

abbijoy2004040

Language

EN