探究大模型在三段论推理中的表现，发现部分模型已接近形式化逻辑水平。
Understanding Syllogistic Reasoning in LLMs from Formal and Natural Language Perspectives
- 从形式逻辑与自然语言双视角分析大模型的三段论推理能力
- 14个模型中部分实现完美符号推理，显示形式化推理能力渐强
- 适合关注大模型推理机制演进的研究者阅读
本文从逻辑学和自然语言两个角度研究大模型的三段论推理能力。为此，我们选取14个大型语言模型，考察其在符号推理与自然语言理解方面的表现。尽管这种推理能力并非所有大模型的统一涌现特性，但部分模型展现出完美的符号推理性能，这引发我们思考：大模型是否正逐渐成为更接近形式化推理的机制，而非显性表达人类推理的细微差别。
原文摘要 · Abstract (English)
We study syllogistic reasoning in LLMs from the logical and natural language perspectives. In process, we explore fundamental reasoning capabilities of the LLMs and the direction this research is moving forward. To aid in our studies, we use 14 large language models and investigate their syllogistic reasoning capabilities in terms of symbolic inferences as well as natural language understanding. Even though this reasoning mechanism is not a uniform emergent property across LLMs, the perfect symbolic performances in certain models make us wonder whether LLMs are becoming more and more formal reasoning mechanisms, rather than making explicit the nuances of human reasoning.
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