RoleBench

Persona-Pruner: framework for sculpting lightweight persona-specific LLM sub-networks via structured pruning

Persona-Pruner is a pruning framework that isolates persona-specific sub-networks from a generalist language model given only a character description, producing lightweight role-playing models without the full model's computational cost. The authors observe that naive pruning degrades role-playing fidelity by failing to distinguish redundant knowledge from character-essential parameters. On RoleBench, Persona-Pruner reduces performance drop by up to 93.8% relative to the strongest baseline pruning method while preserving general LLM capabilities. The work targets practical deployment scenarios such as game ecosystems with many simultaneous NPC agents.