AI RESEARCH

Activation Steering with a Feedback Controller

arXiv CS.LG

ArXi:2510.04309v2 Announce Type: replace Controlling the behaviors of large language models (LLM) is fundamental to their safety alignment and reliable deployment. However, existing steering methods are primarily driven by empirical insights and lack theoretical performance guarantees. In this work, we develop a control-theoretic foundation for activation steering by showing that popular steering methods correspond to the proportional (P) controllers, with the steering vector serving as the feedback signal.