• Vaishnavi D
• Preetham K
• Sudeep Kumar G
• G S Priya
• Pavana H

In the era of rapid digital content expansion, paraphrasing, text summarization, plagiarism detection has become increasingly important for rephrasing information clearly and effectively while preserving its original intent. This review explores cutting-edge AI-based techniques for paraphrasing, text summarization, and plagiarism detection, focusing on methodologies such as deep learning, transformer architectures, and semantic analysis. We consolidate findings from multiple studies, comparing models like BERT, GPT, and sequence-to-sequence frameworks, and evaluate their performance across diverse applications. The paper also highlights the challenges, limitations, and future prospects of integrating these AI tools in educational, legal, and content creation domains, providing a roadmap for researchers and practitioners.

Paraphrasing, Text Summarization, Plagiarism Detection, NLP, Deep Learning, Transformer Models, Artificial Intelligence

"A COMPREHENSIVE REVIEW OF AI-BASED APPROACHES FOR PARAPHRASING, TEXT SUMMARIZATION, PLAGIARISM DETECTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 5, page no.b759-b764, May-2025, Available :http://www.jetir.org/papers/JETIR2505190.pdf

"A COMPREHENSIVE REVIEW OF AI-BASED APPROACHES FOR PARAPHRASING, TEXT SUMMARIZATION, PLAGIARISM DETECTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 5, page no. ppb759-b764, May-2025, Available at : http://www.jetir.org/papers/JETIR2505190.pdf