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TopicsMechanistic Interpretability Large language models

At L0=160, fully trained SAEs significantly outperform frozen variants in most sparse-probing and causal-editing comparisons.

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One-sided Welch t-tests (H0: μ(fully-trained) ≤ μ(frozen); n=3 seeds) across frozen variants in these tables reach significance for Explained Variance in 30/30 comparisons, Sparse Probing (top-1) in 21/30, and Causal Editing in 20/30; for roughly a quarter of downstream comparisons the gap is not statistically significant.

Sanity Checks for Sparse Autoencoders: Do SAEs Beat Random Baselines?conference paperextraction 0.75

Korznikov, Anton et al. · arXiv.org · Feb 15, 2026 · original

Appendix D ablation at L0=160, three seeds

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Created by extractor · Nov 13, 2026. Every judgment on this page is accompanied by a reasoning trace.