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News/Toward Identifiable Sparse Autoencoders
arxiv
PublishedJune 1, 2026 at 4:00 AM

Toward Identifiable Sparse Autoencoders

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arXiv:2605.31245v1 Announce Type: new Abstract: Recently, sparse autoencoders (SAEs) have emerged as an attractive tool for interpreting and interacting with representations in practical neural networks. While it is common empirical folklore, we also show theoretically that SAEs are highly unstable:

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