Plagiarism Detection: Identifying AI-Generated and Paraphrased Content

This report presents a comprehensive analysis of a demo application designed for AI detection and paraphrase detection using state-of-the-art natural language processing (NLP) models. The demo leverages the GPT-2 model for AI detection, evaluating the input text based on perplexity and burstiness scores to determine the likelihood of being generated by an AI. Additionally, the demo integrates a paraphrase detector utilizing BERT (Bidirectional Encoder Representations from Transformers) to identify similarities between input sentences. The GPT-2-based AI detection module assesses the input text's perplexity and burstiness scores, which serve as indicators of language complexity and repetition, respectively. Texts with high perplexity and low burstiness scores are flagged as potentially AI-generated. The paraphrase detection module, powered by BERT, employs semantic similarity techniques to compare input sentences and identify paraphrases or closely related sentences. Through a user-friendly interface, the demo allows users to input text for analysis and receive real-time feedback on AI likelihood and paraphrase similarity. The report provides insights into the implementation details, including the integration of the GPT-2 and BERT models, text preprocessing techniques, and result interpretation.