Neuron-based Personality Trait Induction in Large Language Models

Understand

Large language models (LLMs) have become increasingly proficient at simulating various personality traits, an important capability for supporting related applications (e.g., role-playing).

• To further improve this capacity, in this paper, we present a neuron-based approach for personality trait induction in LLMs, with three major technical contributions.
• First, we construct PersonalityBench, a large-scale dataset for identifying and evaluating personality traits in LLMs.
• This dataset is grounded in the Big Five personality traits from psychology and is designed to assess the generative capabilities of LLMs towards specific personality traits.