DeepPersona: A Generative Engine for Scaling Deep Synthetic Personas

arXiv — cs.LG•Wednesday, November 12, 2025 at 5:00:00 AM

The introduction of DEEPPERSONA represents a significant advancement in the field of artificial intelligence, particularly in the simulation of human profiles through large language models. By employing a two-stage, taxonomy-guided method, DEEPPERSONA constructs the largest-ever human-attribute taxonomy, allowing for the generation of narrative-complete synthetic personas that are far more complex than previous models. Evaluations indicate a 32% increase in attribute diversity and a 44% enhancement in profile uniqueness compared to existing baselines. Furthermore, the use of these advanced personas has led to an 11.6% improvement in the accuracy of personalized question answering by the GPT-4.1-mini model, and a 31.7% reduction in the gap between simulated responses and authentic human interactions. This progress not only enhances the realism of AI-generated personas but also contributes to the broader goal of aligning AI behavior with human expectations.

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