论文标题
在法律文本处理管道中基于Grad-CAM的解释性
Towards Grad-CAM Based Explainability in a Legal Text Processing Pipeline
论文作者
论文摘要
可解释的AI（XAI）是一个专注于提供决策过程的解释性和解释性的领域。在法律领域，除了系统和数据透明度外，它还需要（法律）决策模式透明度以及在达成决定时了解内部工作的模型的能力。本文提供了使用流行的图像处理技术Grad-CAM来展示法律文本的解释性概念的第一个方法。在适应的毕业-CAM指标的帮助下，我们显示了嵌入式选择，对上下文信息的考虑以及它们对下游处理的影响之间的相互作用。
Explainable AI(XAI)is a domain focused on providing interpretability and explainability of a decision-making process. In the domain of law, in addition to system and data transparency, it also requires the (legal-) decision-model transparency and the ability to understand the models inner working when arriving at the decision. This paper provides the first approaches to using a popular image processing technique, Grad-CAM, to showcase the explainability concept for legal texts. With the help of adapted Grad-CAM metrics, we show the interplay between the choice of embeddings, its consideration of contextual information, and their effect on downstream processing.
