1 code implementation • 26 Mar 2024 • Yanran Tang, Ruihong Qiu, Hongzhi Yin, Xue Li, Zi Huang
In a case pool, there are three types of case connectivity relationships: the case reference relationship, the case semantic relationship, and the case legal charge relationship.
1 code implementation • 22 Dec 2023 • Yilun Liu, Ruihong Qiu, Yanran Tang, Hongzhi Yin, Zi Huang
Our prior work, CaT is a replay-based framework with a balanced continual learning procedure, which designs a small yet effective memory bank for replaying data by condensing incoming graphs.
1 code implementation • 18 Dec 2023 • Yanran Tang, Ruihong Qiu, Yilun Liu, Xue Li, Zi Huang
Previous neural legal case retrieval models mostly encode the unstructured raw text of case into a case representation, which causes the lack of important legal structural information in a case and leads to poor case representation; (2) Lengthy legal text limitation.
1 code implementation • 6 Sep 2023 • Yanran Tang, Ruihong Qiu, Xue Li
Although these straightforward methods have achieved improvement over conventional statistical methods in retrieval accuracy, two significant challenges are identified in this paper: (1) Legal feature alignment: the usage of the whole case text as the input will generally incorporate redundant and noisy information because, from the legal perspective, the determining factor of relevant cases is the alignment of key legal features instead of whole text matching; (2) Legal context preservation: furthermore, since the existing text encoding models usually have an input length limit shorter than the case, the whole case text needs to be truncated or divided into paragraphs, which leads to the loss of the global context of legal information.