Large Language Models (LLMs) have become valuable assets in mental health, showing promise in both classification tasks and counseling applications. This paper offers a perspective on using LLMs in mental health applications. It discusses the instability of generative models for prediction and the potential for generating hallucinatory outputs, underscoring the need for ongoing audits and evaluations to maintain their reliability and dependability. The paper also distinguishes between the often interchangeable terms ``explainability'' and ``interpretability'', advocating for developing inherently interpretable methods instead of relying on potentially hallucinated self-explanations generated by LLMs. Despite the advancements in LLMs, human counselors' empathetic understanding, nuanced interpretation, and contextual awareness remain irreplaceable in the sensitive and complex realm of mental health counseling. The use of LLMs should be approached with a judicious and considerate mindset, viewing them as tools that complement human expertise rather than seeking to replace it.

大型语言模型在心理健康方面表现出很大的潜力，但使用它们时需要保持谨慎和考虑，把它们视为辅助人类专业技术而非替代品，因为它们可能产生幻觉般的输出，并且在心理健康咨询中，人类辅导员的情感理解、细致解读和背景意识仍然不可替代。

关于在心理健康应用中重新思考大型语言模型