no code implementations • 20 Feb 2024 • Hyolim Jeon, Dongje Yoo, Daeun Lee, Sejung Son, Seungbae Kim, Jinyoung Han
Despite the increasing demand for AI-based mental health monitoring tools, their practical utility for clinicians is limited by the lack of interpretability. The CLPsych 2024 Shared Task (Chim et al., 2024) aims to enhance the interpretability of Large Language Models (LLMs), particularly in mental health analysis, by providing evidence of suicidality through linguistic content.
