DUMA: a Dual-Mind Conversational Agent with Fast and Slow Thinking
On the map: LLM reasoning → Reasoning for agents, planning and code
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Abstract (arXiv)
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.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Placed in Reasoning for agents, planning and code, one of 17 directions in LLM reasoning. Builds on 8 of its 25 references that are in the map. First posted on arXiv 27 Oct 2023.
Builds on
8 of 25 references.
Closest ancestors · 1
Same direction, newest first
Other references · 7
- 2023Sparks of Artificial General Intelligence: Early experiments with GPT-4cited by 2,579
- 2023A Survey on Large Language Model based Autonomous Agentscited by 2,203
- 2023The Rise and Potential of Large Language Model Based Agents: A Surveycited by 1,422
- 2023HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Facecited by 1,173
- 2022GLM-130B: An Open Bilingual Pre-trained Modelcited by 837
- 2023ExpeL: LLM Agents Are Experiential Learnerscited by 814
- 2023Cognitive Architectures for Language Agentscited by 422
Built on by
Citing papers per year: 2024: 2; 2025: 1; 2026: 1.
4 papers.
- 2024Human-AI Collaborative Essay Scoring: A Dual-Process Framework with LLMscited by 38
- 2025ThinkGuard: Deliberative Slow Thinking Leads to Cautious Guardrailscited by 29
- 2024Thinker-DDM: Modeling Deliberation for Machine Translation with a Drift-Diffusion Processcited by 3
- 2026PersonaDual: Balancing Personalization and Objectivity via Adaptive Reasoningcited by 0
- 2026PersonaDual: Balancing Personalization and Objectivity via Adaptive Reasoning13 Jan 2026
- 2025ThinkGuard: Deliberative Slow Thinking Leads to Cautious Guardrails19 Feb 2025
- 2024Thinker-DDM: Modeling Deliberation for Machine Translation with a Drift-Diffusion Process16 Feb 2024
- 2024Human-AI Collaborative Essay Scoring: A Dual-Process Framework with LLMs12 Jan 2024
Similar, not cited
Close in wording, no citation either way
- 2024Agents Thinking Fast and Slow: A Talker-Reasoner Architecture
- 2025A Desideratum for Conversational Agents: Capabilities, Challenges, and Future Directions
- 2025Reflecting with Two Voices: A Co-Adaptive Dual-Strategy Framework for LLM-Based Agent Decision Making
- 2023Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debate
- 2025Infusing Theory of Mind into Socially Intelligent LLM Agents
- 2025Large Language Models as Theory of Mind Aware Generative Agents with Counterfactual Reflection
- 2026Theory of Mind and Persuasion Beyond Conversation: Assessing the Capacity of LLMs to Induce Belief States via Planning and Action
- 2023FANToM: A Benchmark for Stress-testing Machine Theory of Mind in Interactions