The proposed framework, detailed in a recent ArXiv publication, tackles the challenges faced by single-agent large language model (LLM) systems in behavioral health contexts.
By employing a multi-agent approach, the framework is designed to enhance safety during interactions, which is critical in sensitive behavioral health scenarios.
This innovative architecture not only improves the capacity for diverse conversational functions but also aims to mitigate risks associated with safety in communication.