Maeghal Jain

Dissecting Persona-Driven Reasoning in Language Models via Activation Patching

Large language models (LLMs) exhibit remarkable versatility in adopting diverse personas. In this study, we examine how assigning a persona influences a model’s reasoning on an objective task. Using activation patching, we take a first step toward understanding how key components of the model encode