Internal Mechanisms of a Large Language Model

This March 27, 2025 Anthropic paper provides an overview and detailed excerpts from two related Anthropic papers concerning the **interpretability of large language models**, specifically focusing on Claude 3.5 Haiku. The core objective is to reverse engineer the **internal computational mechanisms**, or "circuits," that drive the model's behavior, analogous to studying biology or neuroscience. The research introduces a **circuit tracing methodology** that uses attribution graphs and feature analysis to examine how the model handles various tasks, including **multi-step reasoning**, **planning in poems**, **multilingual translation**, and **arithmetic**. Findings reveal sophisticated strategies like internal planning and the existence of "default" refusal circuits that must be **inhibited by "known answer" features** for the model to respond to questions, illuminating the mechanisms behind **hallucinations and jailbreaks**.

Sources:

https://transformer-circuits.pub/2025/attribution-graphs/biology.html

https://www.anthropic.com/research/tracing-thoughts-language-model