Evaluating Brain-Inspired Modular Training in Automated Circuit Discovery for Mechanistic Interpretability

Understand

Large Language Models (LLMs) have experienced a rapid rise in AI, changing a wide range of applications with their advanced capabilities.

• As these models become increasingly integral to decision-making, the need for thorough interpretability has never been more critical.
• Mechanistic Interpretability offers a pathway to this understanding by identifying and analyzing specific sub-networks or 'circuits' within these complex systems.
• A crucial aspect of this approach is Automated Circuit Discovery, which facilitates the study of large models like GPT4 or LLAMA in a feasible manner.