Trustworthy & Interpretable AI

We make models understandable and trustworthy — extracting human-interpretable concepts with sparse autoencoders, debiasing representations and generative models, characterizing dataset bias, and improving robustness and domain generalization so models behave reliably beyond their training distribution.