查看文章

The surge in legal text production has amplified the workload for legal professionals, making many tasks repetitive and time-consuming. Furthermore, the complexity and specialized language of legal documents pose challenges not just for those in the legal domain but also for the general public. This emphasizes the potential role and impact of Legal Natural Language Processing (Legal NLP). Although advancements have been made in this domain, particularly after 2015 with the advent of Deep Learning and Large Language Models (LLMs), a systematic exploration of this progress until 2022 is nonexistent. In this research, we perform a Systematic Mapping Study (SMS) to bridge this gap.We aim to provide a descriptive statistical analysis of the Legal NLP research between 2015 and 2022. Categorize and sub-categorize primary publications based on their research problems. Identify limitations and areas of …