The field of natural language processing is moving towards more nuanced and controllable models of personality, with a focus on aligning model behavior with psychological theory. Recent work has explored the use of prototype theory and Big Five personality traits to improve the accuracy and interpretability of personality modeling. Additionally, there is a growing interest in developing methods for controlling and steering model behavior to meet specific needs, such as generating text with desired personality attributes. Notable papers in this area include: Cognitive Alignment in Personality Reasoning: Leveraging Prototype Theory for MBTI Inference, which presents a framework for MBTI inference that operationalizes prototype theory within a language model-based pipeline. Activation-Space Personality Steering: Hybrid Layer Selection for Stable Trait Control in LLMs, which proposes a novel pipeline for extracting hidden state activations from transformer layers and identifying trait-specific optimal layers for robust injection.