A Primer on Computational Semantics for Artificial Intelligence Systems
arXiv:2608.25022v1 Announce Type: new Abstract: As people adopt transformer-based language models (e.g., ChatGPT and Gemini) for an increasing number of use-cases, it is important to know how such models learn and represent the meaning of the language, and to be more informed about what language is. This document is an attempt to help the reader understand how linguistic meaning (i.e., semantics) is approached from different fields of scientific and philosophical examination. I also explain three primary semantic theories: formal semantics, grounded semantics, and distributional semantics then compare how transformer-based language models differ from how humans learn language.
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[Submitted on 25 Aug 2026]
Title:A Primer on Computational Semantics for Artificial Intelligence Systems
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Abstract:As people adopt transformer-based language models (e.g., ChatGPT and Gemini) for an increasing number of use-cases, it is important to know how such models learn and represent the meaning of the language, and to be more informed about what language is. This document is an attempt to help the reader understand how linguistic meaning (i.e., semantics) is approached from different fields of scientific and philosophical examination. I also explain three primary semantic theories: formal semantics, grounded semantics, and distributional semantics then compare how transformer-based language models differ from how humans learn language.
Comments: 23 pages
Subjects:
Computation and Language (cs.CL); Artificial Intelligence (cs.AI)
Cite as: arXiv:2608.25022 [cs.CL]
(or arXiv:2608.25022v1 [cs.CL] for this version)
https://doi.org/10.48550/arXiv.2608.25022
arXiv-issued DOI via DataCite (pending registration)
Submission history
From: Casey Kennington [view email] [v1] Tue, 25 Aug 2026 18:10:04 UTC (751 KB)
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