Inspired by the dual-process theory of human cognition, we introduce DUMA, a novel conversational agent framework that embodies a dual-mind mechanism through the utilization of two generative Large Language Models (LLMs) dedicated to fast and slow thinking respectively. The fast thinking model serves as the primary interface for external interactions and initial response generation, evaluating the necessity for engaging the slow thinking model based on the complexity of the complete response. When invoked, the slow thinking model takes over the conversation, engaging in meticulous planning, reasoning, and tool utilization to provide a well-analyzed response. This dual-mind configuration allows for a seamless transition between intuitive responses and deliberate problem-solving processes based on the situation. We have constructed a conversational agent to handle online inquiries in the real estate industry. The experiment proves that our method balances effectiveness and efficiency, and has a significant improvement compared to the baseline.

翻译：受人类认知双过程理论的启发，我们提出了一种名为DUMA的新型对话智能体框架。该框架通过利用两个分别负责快思维与慢思维的生成式大语言模型，实现了双心智机制。其中，快思维模型作为外部交互与初始响应生成的主要接口，根据完整响应的复杂度评估是否触发慢思维模型。当被调用时，慢思维模型接管对话，通过细致的规划、推理及工具调用，提供经过深思熟虑的回应。这种双心智配置使得智能体能够根据情境在直觉响应与审慎问题求解过程之间无缝切换。我们构建了一个用于处理房地产行业在线咨询的对话智能体。实验证明，该方法实现了有效性与效率的平衡，相较于基线方法取得了显著提升。