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TopicsMechanistic Interpretability Latent Knowledge in Language Models Large language models

SAE-based sparse probes underperform plain logistic regression on language-model activations under data scarcity, label noise, and covariate shift.

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Kantamneni et al. [16] report that SAE-based sparse probes underperform plain logistic regression across data scarcity, label noise, and covariate shift

Are Sparse Autoencoder Benchmarks Reliable?preprintextraction 0.85

Chanin, David · arXiv.org · May 18, 2026 · original

Related work, 'Cases where supervised baselines beat SAEs'; also intro: 'recent work has called into question the quality of SAEs compared to supervised baselines [16, 32]'

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