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@article{180216,
        author = {Sakshi Pujari and Mahesh Vanjire and Isha Ruplag and Riya Patankar},
        title = {Text Summarization Using NLP},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {1},
        pages = {849-850},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=180216},
        abstract = {Automatic text summarization aims to condense lengthy documents into concise summaries while preserving key information. With the rise of transformer-based architectures, abstractive summarization has made significant advances. This paper presents a comparative study of pop- ular models such as BART, T5, and PEGASUS on standard datasets like CNN/DailyMail and XSum. We evaluate their performance using ROUGE and BERTScore, and analyze their strengths and limitations.},
        keywords = {},
        month = {June},
        }