A Syllogistic Probe: Tracing the Evolution of Logic Reasoning in Large Language Models

• URL: http://arxiv.org/abs/2601.17426v1
• Date: Sat, 24 Jan 2026 11:51:52 GMT
• Title: A Syllogistic Probe: Tracing the Evolution of Logic Reasoning in Large Language Models
• Authors: Zhengqing Zang, Yuqi Ding, Yanmei Gu, Changkai Song, Zhengkai Yang, Guoping Du, Junbo Zhao, Haobo Wang,
• Abstract summary: We explore whether large language models (LLMs) exhibit a similar evolution in the underlying logical framework.<n>Using existential import as a probe, we evaluate syllogism under traditional and modern logic.
• Score: 17.118221176971982
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Human logic has gradually shifted from intuition-driven inference to rigorous formal systems. Motivated by recent advances in large language models (LLMs), we explore whether LLMs exhibit a similar evolution in the underlying logical framework. Using existential import as a probe, we for evaluate syllogism under traditional and modern logic. Through extensive experiments of testing SOTA LLMs on a new syllogism dataset, we have some interesting findings: (i) Model size scaling promotes the shift toward modern logic; (ii) Thinking serves as an efficient accelerator beyond parameter scaling; (iii) the Base model plays a crucial role in determining how easily and stably this shift can emerge. Beyond these core factors, we conduct additional experiments for in-depth analysis of properties of current LLMs on syllogistic reasoning.

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