Notes on the Mathematical Structure of GPT LLM Architectures
Spencer Becker-Kahn
TL;DR
This paper explores the mathematical foundations of GPT-3-style large language models, providing insights into their neural network architecture and underlying structure.
Contribution
It offers a detailed mathematical analysis of GPT-like architectures, highlighting their structural properties and theoretical underpinnings.
Findings
Mathematical characterization of GPT architecture
Insights into neural network layer interactions
Foundations for future theoretical work
Abstract
An exposition of the mathematics underpinning the neural network architecture of a GPT-3-style LLM.
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Taxonomy
TopicsAdvanced Database Systems and Queries · Scientific Computing and Data Management · Data Mining Algorithms and Applications