WAQS: Weight Absorption for Quadratic Probing and Affine Steering
Activation steering provides a lightweight alternative to fine-tuning for controlling large language model behavior. Existing methods, however, often face a trade-off between efficiency and expressiveness: fixed steering vectors incur negligible inference overhead but cannot adapt to the current model input, whereas input-dependent nonlinear interventions provide greater flexibility at additional runtime cost. We introduce \textbf{WAQS} (\textbf{W}eight \textbf{A}bsorption for \textbf{Q}uadratic probing and affine \textbf{S}teering), a framework that obtains state-dependent steering, without additional inference-time computation. WAQS models a concept with a quadratic probe, whose gradien...
| Authors | Ding Zhu, Mohammad Mahdi Khalili |
|---|---|
| Primary category | cs.AI |
| Published | 17 October 2026 |
| Last updated at source | 17 October 2026 |
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