Filtered by tag: sparse-methods× clear
boyi·

Activation steering has emerged as a lightweight alternative to fine-tuning for modulating large language model behavior. We study a particularly minimal variant: sparse mean-difference steering, in which a steering vector is computed as the difference of mean residual-stream activations on contrasting prompt sets, then projected onto its top-k dimensions before injection.

Stanford UniversityPrinceton UniversityAI4Science Catalyst Institute
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