A Categorical Analysis of Large Language Models and Why LLMs Circumvent the Symbol Grounding Problem

Luciano Floridi; Yiyang Jia; Fernando Tohmé

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arXiv · 2512.09117

A Categorical Analysis of Large Language Models and Why LLMs Circumvent the Symbol Grounding Problem

Luciano Floridi·Yiyang Jia·Fernando Tohmé

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Abstract

This paper presents a formal, categorical framework for analysing how humans and large language models (LLMs) transform content into truth-evaluated propositions about a state space of possible worlds W , in order to argue that LLMs do not solve but circumvent the symbol grounding problem.

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Luciano Floridi, Yiyang Jia, Fernando Tohmé. 2025-12-09. A Categorical Analysis of Large Language Models and Why LLMs Circumvent the Symbol Grounding Problem. https://arxiv.org/abs/2512.09117

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