← 研踪 PaperTrailACL Anthology · ACL 2026:acl:2026.acl-long.2098 · 记录 #1
Legal Judgment Prediction: A Reflection on the State of the Art
来源日期(仅到月份) 2026-07
来源记录日期 2026-07
雷达观测 2026-11-01 21:46
摘要
Automatic legal judgment prediction (LJP) has recently received increasing attention in the natural language processing community because of its practical values in the real world. Significant progress has been achieved on LJP in the past decade. However, most existing LJP research primarily focuses on developing methods that achieve better performance on standard evaluation datasets, with limited emphasis on the long-term advancement of the field beyond improving evaluation metrics. In this position paper, we reflect on the state of the art in LJP research, and explore issues that should motivate researchers to think beyond merely enhancing performance metrics, with the ultimate goal of sparking discussions among LJP researchers about the future trajectory of the field.
论文发现出处
这些页面提供论文线索,不代表同行评审或质量认证。
观测到的版本
平台记录号代表本站观测到的元数据变化,不是作者修订号。来源日期仅到月份或年份时,按该月或该年首日存档。
记录 #1 · 2026-07 · 最新观测版本
Legal Judgment Prediction: A Reflection on the State of the Art
Automatic legal judgment prediction (LJP) has recently received increasing attention in the natural language processing community because of its practical values in the real world. Significant progress has been achieved on LJP in the past decade. However, most existing LJP research primarily focuses on developing methods that achieve better performance on standard evaluation datasets, with limited emphasis on the long-term advancement of the field beyond improving evaluation metrics. In this position paper, we reflect on the state of the art in LJP research, and explore issues that should motivate researchers to think beyond merely enhancing performance metrics, with the ultimate goal of sparking discussions among LJP researchers about the future trajectory of the field.
查看此版本解读 →查看此版本原文 ↗