Large language models (LLMs) demonstrate strong language generation capabilities but often struggle with structured reasoning, leading to inconsistent or suboptimal problem-solving. To mitigate this limitation, Guilford's Structure of Intellect (SOI) model - a foundational framework from intelligence theory - is leveraged as the basis for cognitive prompt engineering. The SOI model categorizes cognitive operations such as pattern recognition, memory retrieval, and evaluation, offering a systematic approach to enhancing LLM reasoning and decision-making. This position paper presents a novel cognitive prompting approach for enforcing SOI-inspired reasoning for improving clarity, coherence, and adaptability in model responses.

翻译：大型语言模型（LLMs）展现出强大的语言生成能力，但在结构化推理方面常存在困难，导致问题解决不一致或欠佳。为缓解这一局限，本研究利用吉尔福德的智力结构（SOI）模型——一种源自智力理论的基础框架——作为认知提示工程的基础。SOI模型对模式识别、记忆提取和评估等认知操作进行分类，为增强LLM的推理与决策能力提供了系统化方法。本立场论文提出一种新颖的认知提示方法，通过强制执行受SOI启发的推理机制，以提升模型响应的清晰度、连贯性与适应性。