Notes on the Mathematical Structure of GPT LLM Architectures

This work offers a theoretical explanation for researchers and practitioners interested in understanding the mathematical basis of existing LLM architectures, but it is incremental as it does not introduce new methods or data.

The paper provides an exposition of the mathematical structure underlying GPT-3-style large language model architectures, explaining the foundational principles without presenting new experimental results or numerical improvements.