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News/When Structured Sparse Autoencoders Learn Consistent Concepts Across Modalities
arxiv
PublishedJuly 10, 2026 at 4:00 AM
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When Structured Sparse Autoencoders Learn Consistent Concepts Across Modalities

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arXiv:2607.08605v1 Announce Type: cross Abstract: Sparse autoencoders (SAEs) have emerged as a promising technique for mechanistic interpretability by learning a set of sparse latent features in large models, each of which encodes a distinct concept. However, in vision-language models (VLMs), vanill

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