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TopicsMechanistic Interpretability AI Capability Evaluation

Passing standard SAE benchmarks does not establish meaningful decomposition of LLM activations.

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On real LLM activations, our frozen baselines match fully-trained SAEs across reconstruction, interpretability, sparse probing, and causal editing, showing that passing standard benchmarks is not sufficient evidence of meaningful feature decomposition.

Sanity Checks for Sparse Autoencoders: Do SAEs Beat Random Baselines?conference paperextraction 0.80

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

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