A Primer on Computational Semantics for Artificial Intelligence Systems
Casey Kennington
cs.CL cs.AI
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.
Topics
Classified with taxonomy v2 on Sat, 5 Sept 2026.