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DUMA，一种新颖的对话智能体框架。该框架通过分别专用于快速思考与慢速思考的两个生成式大规模语言模型，实现了双心智机制。快速思考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程度评估是否需要调用慢速思考模型。当被调用时，慢速思考模型将接管对话，进行细致的规划、推理与工具调用，以提供经过充分分析的响应。这种双心智配置使得智能体能够根据情境在直觉式响应与审慎式问题解决过程之间无缝切换。我们构建了一个处理房地产行业在线咨询的对话智能体。实验证明，本方法在有效性与效率之间取得了平衡，相比基线方法有显著提升。