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@article{177879,
        author = {Veer Yadav and Khushal Vashishth and Sambhav Jain},
        title = {Enhancing Abstractive Text Summarization for Legal Documents and Court Verdicts},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {3041-3049},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=177879},
        abstract = {This research initiative seeks to synergize the advancements in abstractive text summarization techniques with a laser-focused application on the realm of legal documents and court verdicts. The primary objective is to spearhead the development of cutting-edge NLP models and sophisticated algorithms specifically tailored to the formidable challenges posed by the intricate nature of legal texts. The ultimate goal is to render these often convoluted and extensive legal documents in a manner that is not only concise but also highly comprehensible, thus catering to the needs of legal professionals, researchers, and the wider public audience.
The ramifications of this research extend far beyond the confines of the legal domain. The ability to generate precise, yet intelligible summaries of lengthy legal texts has significant implications for facilitating decision-making processes, expediting legal research, and improving overall access to legal information. Furthermore, this research could bridge a critical gap between the intricacies of the law and the broader society, promoting transparency and accessibility within the legal field and potentially paving the way for innovative legaltech applications.},
        keywords = {},
        month = {May},
        }