The count of pending cases has shown an exponential rise across nations (e.g., with more than 10 million pending cases in India alone). The main issue lies in the fact that the number of cases submitted to the law system is far greater than the available number of legal professionals present in a country. Given this worldwide context, the utilization of AI technology has gained paramount importance to enhance the efficiency and speed of legal procedures. In this study we partcularly focus on helping legal professionals in the process of analyzing a legal case. Our specific investigation delves into harnessing the generative capabilities of open-sourced large language models to create arguments derived from the facts present in legal cases. Experimental results show that the generated arguments from the best performing method have on average 63% overlap with the benchmark set gold standard annotations.

翻译：全球各国的待审案件数量呈指数级增长（例如，仅印度就有超过1000万件待审案件）。主要问题在于，提交至司法系统的案件数量远超该国可用的法律专业人员数量。在这一全球背景下，利用人工智能技术来提升法律程序的效率与速度已变得至关重要。本研究重点关注如何协助法律专业人员分析法律案件。我们的具体研究旨在探索利用开源大型语言模型的生成能力，从法律案件中的事实出发生成论证。实验结果表明，性能最佳的方法生成的论证，与基准数据集的金标准标注平均有63%的重叠率。