Enhancing the Generation of Legal Case Headnotes with Expanded Abstractive Summarization Models

Legal case headnotes play a vital role in briefing about the cases. Automation of headnotes summarization is very
crucial because of the legal language used in the case briefing. There are many transformer-based models like
PEGASUS, BART & T5 for summarizing the legal texts. The above models are refined to a specific legal dataset
which will investigate a combined approach of strategy which includes extractive summarization models to
enhance the quality of summarizing the legal head notes which also holds in line with the limitation of the
abstractive summarization approaches. When this method of approach is applied a summary system of legal
headnotes will be implemented. By offering strong tools for legal text summarizing, this study is expected to
advance the field of legal technology, expedite legal research procedures, and increase accessibility to legal
information