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TopicsSparse Autoencoders Mechanistic Interpretability Latent Knowledge in Language Models

Max-pooled SAE probes outperform single-token raw-activation probes on labeled concepts in multi-token text.

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Alternatively, if inference-time compute is limited, we find SAE-based probing methods outperform raw activation probing.

Investigating task-specific prompts and sparse autoencoders for activation monitoringpreprintextraction 0.85

Tillman, Henk, Mossing, Dan · arXiv.org · Apr 28, 2025 · original

Abstract; repeated in contributions: 'Our results agree with Bricken et al. (2024) that max-pooled SAE activation probing outperforms raw activation probing.' Results on GPT-4o activations across moderation, SimpleQA hallucination, and sentiment tasks.

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