Controlling Refusal Behavior of LLMs via Stiefel-Constrained Rotation Steering
On the map: Mechanistic interpretability → Steering and probing for LLM safety
Abstract (arXiv)
Activation steering has emerged as a lightweight approach for controlling model refusal at inference time. A growing line of research explores trainable rotations of activations to develop geometrically principled intervention mechanisms. However, existing techniques rely on auxiliary constructs, such as refusal vectors, to define these rotations. In our work, we develop a self-contained methodology for learning parameter-efficient rotational transformations based on Riemannian optimization. We empirically validate the proposed scheme, demonstrating its superiority in intervention efficiency. An extensive ablation study highlights the importance of key design choices in our method. Our results identify the proposed rotation-based steering scheme as a promising direction for more reliable control over the behavior of LLMs.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Steering and probing for LLM safety, one of 13 directions in Mechanistic interpretability. Builds on 25 of its 31 references that are in the map. First posted on arXiv 31 Aug 2026.
Builds on
25 of 31 references.
Closest ancestors · 2
Same direction, newest first
- 2025Beyond I'm Sorry, I Can't: Dissecting Large Language Model Refusal7 Sep
- 2025AlphaSteer: Learning Refusal Steering with Principled Null-Space Constraint8 Jun
Other references · 23
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11 more
- 2024Personalized Steering of Large Language Models: Versatile Steering Vectors Through Bi-directional Preference Optimizationcited by 118
- 2025The Geometry of Refusal in Large Language Models: Concept Cones and Representational Independencecited by 115
- 2025LLMs Encode Harmfulness and Refusal Separatelycited by 88
- 2023Eight Things to Know about Large Language Modelscited by 73
- 2025Angular Steering: Behavior Control via Rotation in Activation Spacecited by 53
- 2024Refusal in LLMs is an Affine Functioncited by 29
- 2024Householder Pseudo-Rotation: A Novel Approach to Activation Editing in LLMs with Direction-Magnitude Perspectivecited by 23
- 2026Spherical Steering: Geometry-Aware Activation Rotation for Language Modelscited by 21
- 2025SOM Directions are Better than One: Multi-Directional Refusal Suppression in Language Modelscited by 9
- 2026Selective Steering: Norm-Preserving Control Through Discriminative Layer Selectioncited by 6
- 2026Minimizing Collateral Damage in Activation Steeringcited by 5
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Not cited yet.
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