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@article{202639,
        author = {Sonali Waje and Dr. C. M. Raut},
        title = {Transformer Based Approaches for Marathi Abstractive Summarization: A Comparative Analysis},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {8678-8683},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=202639},
        abstract = {Automatic Text Summarization (ATS) is a significant task in the field of Natural Language Processing (NLP), aimed at generating concise and meaningful summaries from large textual content. In recent years, ATS has grabbed attention of many researchers because of large volumes of information which is readily available in multiple languages on a digital platform. Automatically generating precise summaries from large text has potential application in generation of news headlines, summary of research articles, financial research, chatbots etc. While English text summarization has achieved substantial progress due to abundant datasets and pretrained models, Marathi and other Indian regional languages remain underrepresented in research. Marathi language poses special difficulties for Natural Language Processing due to rich morphology and intricate syntactic patterns. This study focuses on comparison of different transformer-based model.},
        keywords = {Abstractive Text summarization (ATS), Transformer Models, IndicBART, mBART, mT5, Marathi language.},
        month = {May},
        }