Problem
Research questions and friction points this paper is trying to address.
computational semantics
transformer-based language models
linguistic meaning
A Primer on Computational Semantics for Artificial Intelligence Systems
🤖 AI Summary
本文探讨了基于变换器的语言模型如何学习和表示语言意义，并介绍了三种主要的语义理论，比较了这些模型与人类学习语言方式的区别。
📝 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.
Innovation
Methods, ideas, or system contributions that make the work stand out.
computational semantics
transformer-based language models
semantic theories
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