Enhancing Persona Following at Decoding Time via Dynamic Importance Estimation for Role-Playing Agents

Researchers propose a new Persona Dynamic Decoding (PDD) framework that enables AI role-playing agents to dynamically adapt their personas based on context during inference time. The method uses psychological theories to estimate persona importance and adjust behavior without requiring expensive fine-tuning or static prompts.