PERSONAWEAVER: Controllable Diversity Beyond Conventional Archetypes in Procedural Character Generation

Excerpt

arXiv:2609.26629v1 Announce Type: new Abstract: Procedural character generation aims to populate games, simulations, and other virtual worlds with diverse characters. Large language models (LLMs) offer a promising foundation for scaling this task. However, LLM-based procedural character generation remains at an early stage: existing methods either generate characters directly or adapt profiles retrieved from persona banks. As we show, both approaches produce behaviorally homogeneous populations: