A Mathematical Framework for Transformer Circuits

This post introduces a mathematical framework for analyzing transformer circuits, specifically focusing on how specific computations (circuits) emerge from the network's architecture and training. It proposes a method to identify and analyze these circuits by examining the activation patterns of individual components (like attention heads and MLP layers) and their interactions. The framework aims to provide a more rigorous and systematic way to understand the internal workings of LLMs, moving beyond anecdotal observations to formal circuit analysis.