Human intelligence thrives on the concept of cognitive synergy, where collaboration and information integration among different cognitive processes yield superior outcomes compared to individual cognitive processes in isolation. Although Large Language Models (LLMs) have demonstrated promising performance as general task-solving agents, they still struggle with tasks that require intensive domain knowledge and complex reasoning. In this work, we propose Solo Performance Prompting (SPP), which transforms a single LLM into a cognitive synergist by engaging in multi-turn self-collaboration with multiple personas. A cognitive synergist refers to an intelligent agent that collaborates with multiple minds, combining their individual strengths and knowledge, to enhance problem-solving and overall performance in complex tasks. By dynamically identifying and simulating different personas based on task inputs, SPP unleashes the potential of cognitive synergy in LLMs. We have discovered that assigning multiple, fine-grained personas in LLMs elicits better problem-solving abilities compared to using a single or fixed number of personas. We evaluate SPP on three challenging tasks: Trivia Creative Writing, Codenames Collaborative, and Logic Grid Puzzle, encompassing both knowledge-intensive and reasoning-intensive types. Unlike previous works, such as Chain-of-Thought, that solely enhance the reasoning abilities in LLMs, SPP effectively elicits internal knowledge acquisition abilities, reduces hallucination, and maintains strong reasoning capabilities. Code, data, and prompts can be found at: https://github.com/MikeWangWZHL/Solo-Performance-Prompting.git.

翻译：人类智能因认知协同概念而蓬勃发展，不同认知过程之间的协作与信息整合所产生的成果优于单独认知过程。尽管大型语言模型（LLMs）作为通用任务解决智能体已展现出令人期待的表现，但在需要密集领域知识和复杂推理的任务中仍面临挑战。本研究提出单人性能提示（SPP），通过使单个LLM与多个角色进行多轮自我协作，将其转化为认知协同者。认知协同者指一种与多个心智协作的智能体，通过整合个体优势与知识，提升复杂任务中的问题解决能力和整体表现。基于任务输入动态识别并模拟不同角色，SPP释放了LLM中认知协同的潜力。我们发现，相较于使用单一或固定数量角色，为LLM分配多个细粒度角色能激发更优的问题解决能力。我们在三项挑战性任务上评估SPP：趣味创意写作、代号协作和逻辑网格谜题，涵盖知识密集型和推理密集型两类任务。与仅提升LLM推理能力的思维链等先前工作不同，SPP有效激发内部知识获取能力、减少幻觉并维持强大推理能力。相关代码、数据和提示可访问：https://github.com/MikeWangWZHL/Solo-Performance-Prompting.git。