Sparse Autoencoders Reveal Interpretable Features in Frontier Multimodal Models

arXiv:2503.14088

Interpretability Research Collective

We scale sparse autoencoder interpretability techniques to frontier multimodal models, recovering monosemantic features that enable precise activation steering for safety-relevant behaviors without full fine-tuning.