Public articles linked to the same research event.
arXiv This survey organizes and analyzes the literature on large language models in mental health around a central thesis: their role is evolving through three increasingly sophisticated phases—Phase I as passive Information Tools and Pattern Recognizers for assessment and risk detection, Phase II as Empathetic Conversationalists for in-the-moment, stateless interactions, and Phase III as Longitudinal, Personalized Companions implemented as stateful cognitive agents—while systematically reviewing the core technologies, agent architectures (Profile, Memory, Reasoning, Planning, Tool Use), datasets, and benchmarks that underpin this trajectory, arguing the field is shifting from one-shot help to long-term companionship.
This survey organizes and analyzes the literature on large language models in mental health around a central thesis: their role is evolving through three increasingly sophisticated phases—Phase I as passive Information Tools and Pattern Recognizers for assessment and risk detection, Phase II as Empathetic Conversationalists for in-the-moment, stateless interactions, and Phase III as Longitudinal, Personalized Companions implemented as stateful cognitive agents—while systematically reviewing the core technologies, agent architectures (Profile, Memory, Reasoning, Planning, Tool Use), datasets, and benchmarks that underpin this trajectory, arguing the field is shifting from one-shot help to long-term companionship.
This survey organizes and analyzes the literature on large language models in mental health around a central thesis: their role is evolving through three increasingly sophisticated phases—Phase I as passive Information Tools and Pattern Recognizers for assessment and risk detection, Phase II as Empathetic Conversationalists for in-the-moment, stateless interactions, and Phase III as Longitudinal, Personalized Companions implemented as stateful cognitive agents—while systematically reviewing the core technologies, agent architectures (Profile, Memory, Reasoning, Planning, Tool Use), datasets, and benchmarks that underpin this trajectory, arguing the field is shifting from one-shot help to long-term companionship.
This survey organizes and analyzes the literature on large language models in mental health around a central thesis: their role is evolving through three increasingly sophisticated phases—Phase I as passive Information Tools and Pattern Recognizers for assessment and risk detection, Phase II as Empathetic Conversationalists for in-the-moment, stateless interactions, and Phase III as Longitudinal, Personalized Companions implemented as stateful cognitive agents—while systematically reviewing the core technologies, agent architectures (Profile, Memory, Reasoning, Planning, Tool Use), datasets, and benchmarks that underpin this trajectory, arguing the field is shifting from one-shot help to long-term companionship.