Probing Persona-Dependent Preferences in Language Models
Researchers found that large language models use an internal 'preference vector' to adopt different personas. This vector is an evaluative representation that tracks how a model prefers certain tasks or behaviors across various contexts and personas, suggesting a shared underlying mechanism for diverse model behaviors.