March 5, 2024, 2:52 p.m. | Zhongxiang Sun, Kepu Zhang, Weijie Yu, Haoyu Wang, Jun Xu

cs.CL updates on arXiv.org arxiv.org

arXiv:2403.01457v1 Announce Type: cross
Abstract: In this paper, we address the issue of using logic rules to explain the results from legal case retrieval. The task is critical to legal case retrieval because the users (e.g., lawyers or judges) are highly specialized and require the system to provide logical, faithful, and interpretable explanations before making legal decisions. Recently, research efforts have been made to learn explainable legal case retrieval models. However, these methods usually select rationales (key sentences) from the …

abstract arxiv case cs.cl cs.ir issue judges lawyers legal logic paper results retrieval rules type

Senior Machine Learning Engineer

@ GPTZero | Toronto, Canada

ML/AI Engineer / NLP Expert - Custom LLM Development (x/f/m)

@ HelloBetter | Remote

Doctoral Researcher (m/f/div) in Automated Processing of Bioimages

@ Leibniz Institute for Natural Product Research and Infection Biology (Leibniz-HKI) | Jena

Seeking Developers and Engineers for AI T-Shirt Generator Project

@ Chevon Hicks | Remote

Principal Data Architect - Azure & Big Data

@ MGM Resorts International | Home Office - US, NV

GN SONG MT Market Research Data Analyst 11

@ Accenture | Bengaluru, BDC7A