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News/Persistent Sparse Autoencoders: Learning Feature-Specific Timescales in Language Model Representations
arxiv
PublishedSeptember 3, 2026 at 4:00 AM
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Persistent Sparse Autoencoders: Learning Feature-Specific Timescales in Language Model Representations

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arXiv:2607.17117v2 Announce Type: replace-cross Abstract: Sparse autoencoders (SAEs) decompose language model activations into sparse features, yet these models traditionally encode each token independently, failing to expose information that persists across a sequence. We first show that temporal p

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