# MidSteer: Optimal Affine Framework for Steering Generative Models

arXiv: https://arxiv.org/abs/2605.05220 · HTML: https://mlsanity.com/paper/2605.05220/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 0 of its 32 references that are in the map.
- First posted on arXiv 17 Apr 2026.

## Abstract (arXiv)

Steering intermediate representations has emerged as a powerful strategy for controlling generative models, particularly in post-deployment alignment and safety settings. However, despite its empirical success, it currently lacks a comprehensive theoretical framework. In this paper, we bridge this gap by formalizing the theory of concept steering. First, we establish a link between steering and affine concept erasure, proving that the standard approach for removing unwanted behaviors is a special case of LEACE (a closed-form method for affine erasure). Next, we formulate a principled theoretical framework for concept switching, LEACE-Switch, and characterize the assumptions under which it provides an optimal affine solution. Building on this analysis, we then introduce MidSteer (Minimal Disturbance concept Steering), a more general affine framework for concept manipulation that relaxes these assumptions and enables directed, minimal-disturbance transformations. We demonstrate that MidSteer performs favorably across a range of tasks, modalities, and architectures, including vision diffusion models and large language models.