Towards Interpretable Mental Health Analysis with Large Language Models

Understand

The latest large language models (LLMs) such as ChatGPT, exhibit strong capabilities in automated mental health analysis.

• However, existing relevant studies bear several limitations, including inadequate evaluations, lack of prompting strategies, and ignorance of exploring LLMs for explainability.
• To bridge these gaps, we comprehensively evaluate the mental health analysis and emotional reasoning ability of LLMs on 11 datasets across 5 tasks.
• We explore the effects of different prompting strategies with unsupervised and distantly supervised emotional information.