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ReLU or TopK θ= (W enc, Wdec,b enc,b dec)parameter tuple of an SAE Θclass of SAEs under consideration Data generating process V= (v 1,

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cs.LG 1

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2026 1

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The Rate-Distortion-Polysemanticity Tradeoff in SAEs

cs.LG · 2026-05-14 · unverdicted · novelty 6.0

SAEs exhibit a rate-distortion-polysemanticity tradeoff where monosemanticity increases rate and distortion, with optimal polysemanticity set by feature co-occurrence probabilities in the data.

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  • The Rate-Distortion-Polysemanticity Tradeoff in SAEs cs.LG · 2026-05-14 · unverdicted · none · ref 18

    SAEs exhibit a rate-distortion-polysemanticity tradeoff where monosemanticity increases rate and distortion, with optimal polysemanticity set by feature co-occurrence probabilities in the data.