This article provides a systematic up-to-date survey of automatic summarization techniques, datasets, models, and evaluation methods in the legal domain. Through specific source selection criteria, we thoroughly review over 120 papers spanning the modern `transformer' era of natural language processing (NLP), thus filling a gap in existing systematic surveys on the matter. We present existing research along several axes and discuss trends, challenges, and opportunities for future research.

翻译：本文对法律领域自动摘要技术、数据集、模型及评估方法进行了系统性的最新综述。通过特定的文献筛选标准，我们全面回顾了涵盖自然语言处理（NLP）现代"Transformer"时代的120余篇论文，从而填补了该领域现有系统性综述的空白。我们从多个维度梳理现有研究，并探讨未来研究的趋势、挑战与机遇。