PRecG: Legal Precedent Retrieval with Graph Neural Networks and Rhetorical Role Segmentation
A new paper introduces PRecG, a method for legal precedent retrieval that uses graph neural networks and rhetorical role segmentation to capture nuanced legal meanings. Unlike existing approaches that treat documents as monolithic texts, PRecG models the rhetorical structure of legal cases, improving retrieval accuracy by distinguishing the contextual significance of legal entities.
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