Understanding Syllogistic Reasoning in LLMs from Formal and Natural Language Perspectives
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.
694a4167335742716e93239a
Aheli Poddar
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2025-12-25T20:47:45.771Z
683bd3b1c15aff506f630819
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Aheli Poddar
xaheli
user
xaheli
694a4167335742716e93239b
Saptarshi Sahoo
694a4167335742716e93239c
Sujata Ghosh
Understanding Syllogistic Reasoning in LLMs from Formal and Natural Language Perspectives
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.
Research explores syllogistic reasoning in LLMs, examining their symbolic inference and natural language understanding capabilities, with some models showing perfect symbolic performance.
syllogistic reasoning large language models symbolic inferences natural language understanding