research
Researchers develop inference-time personality sliders for LLMs without retraining
Researchers have developed a parameter-efficient method to control LLM personalities at inference time using Sequential Adaptive Steering (SAS), which orthogonalizes steering vectors to avoid interference when adjusting multiple traits simultaneously. The approach allows users to modulate the Big Five personality dimensions by adjusting numerical coefficients without retraining models.