Detection and Classification of ChatGPT Generated Contents Using Deep Transformer Models
The scope of this manuscript covers the use of machine learning and deep learning models to detect and classify AI-generated text, with a particular focus on maintaining academic integrity in computer science. It also includes the creation and public release of a dataset comprising human and AI-generated content. The work also compares these models with existing solutions like Turnitin's AI plagiarism detector, contributing to a robust baseline for identifying AI-generated content in academia.
Email Address of Submitting Authormahdi.firstname.lastname@example.org
Submitting Author's InstitutionAnglia Ruskin University
Submitting Author's Country
- United Kingdom