Audio note: this article contains 76 uses of latex notation, so the narration may be difficult to follow. There's a link to the original text in the episode description.

Refer to the arXiv preprint for full content. This post is a lighter, 15-minute version.

Abstract

Existing activation steering methods alter LLM behavior indiscriminately, limiting their practical applicability in settings where selective responses are essential, such as content moderation or domain-specific assistants.
We propose Conditional Activation Steering (CAST), which analyzes LLM activation patterns during inference to selectively apply or withhold activation steering based on the input context.
Using CAST, one can systematically control LLM behavior with rules like “if input is about hate speech or adult content, then refuse” or “if input is not about legal advice, then refuse.”
This allows for selective modification of responses to specific content while maintaining normal responses to other content, all [...]