Full Professor, Cornell University
2 papers at NeurIPS 2025
This paper presents a stylized model of the regulator's choice of an open-source definition in order to evaluate which standards will establish appropriate economic incentives for foundation model developers.
We introduce a mathematical framework and benchmark to quantify generative-model steerability, reveal large steerability gaps in LLMs and text-to-image models, and show that simple mechanisms can improve steerability.
