Aligning Large Language Models for Enhancing Psychiatric Interviews through Symptom Delineation and Summarization

arXiv:2403.17428v1 Announce Type: cross
Abstract: Recent advancements in Large Language Models (LLMs) have accelerated their usage in various domains. Given the fact that psychiatric interviews are goal-oriented and structured dialogues between the professional interviewer and the interviewee, it is one of the most underexplored areas where LLMs can contribute substantial value. Here, we explore the use of LLMs for enhancing psychiatric interviews, by analyzing counseling data from North Korean defectors with traumatic events and mental health issues. Specifically, we investigate …

abstract arxiv cs.ai cs.cl domains interviews language language models large language large language models llms professional summarization through type usage