论文标题
Arglegalsumm：通过参数挖掘改进法律文档的抽象性摘要
ArgLegalSumm: Improving Abstractive Summarization of Legal Documents with Argument Mining
论文作者
论文摘要
生成法律文件摘要时，一项艰巨的任务是解决其论证性质的能力。我们介绍了一种简单的技术，可以通过将论点角色标签整合到摘要过程中来捕获法律文档的论证结构。预算力的语言模型的实验表明，我们提出的方法改善了强大基线的性能
A challenging task when generating summaries of legal documents is the ability to address their argumentative nature. We introduce a simple technique to capture the argumentative structure of legal documents by integrating argument role labeling into the summarization process. Experiments with pretrained language models show that our proposed approach improves performance over strong baselines
