Mohankrishna Kothapalli

Measuring the Predictive Horizon: How Far Can Local Explanations Forecast Autoregressive Language Model Behavior?

Mechanistic interpretability aims to reverse-engineer Large Language Models (LLMs) into human-understandable components, assuming that these components can predict and control model behavior. We challenge this assumption by demonstrating that autoregressive generation exhibits chaotic dynamics and Rashomon multiplicity...