The Steering Budget: Examples Outperform Knobs in Generative Model Control
A new preprint introduces the concept of a 'steering budget' in generative models, determined by the training data, which limits how far properties can be adjusted using conventional controls like prompts or guidance scales. The authors demonstrate that providing concrete examples enables steering across a much larger range than knobs alone, especially for targets that are difficult to specify verbally. They validate these findings in both image and crystal-structure generation tasks, offering a practical method to audit and exploit the steering budget.
Why it matters: This work identifies a fundamental constraint in how generative models can be controlled and proposes a more effective, principled approach for achieving broader and more expressive model steering.
Full story at: arXiv AI/ML ↗