mental health

From Pattern Recognizers to Personalized Companions: A Survey of Large Language Models in Mental Healtharxiv.org

The paper surveys the rapidly growing literature on applying large language models to mental health, organizing it into three evolutionary phases from passive information tools to stateful personalized companions. It reviews core technologies, agent architectures, datasets, and benchmarks, and outlines challenges and a roadmap for responsible, effective AI‑driven mental health support.