Scoring Explanations Without Reading Them: Structural Shortcuts in Automated-Interpretability Evaluation Data
arXiv:2610.37676v1 Announce Type: new Abstract: Automated interpretability scores an explanation of a sparse-autoencoder (SAE) feature by asking a model to predict, token by token, where the feature fires on evaluation examples or to judge whether marked tokens fit it. We find that the evaluation d…
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- 2026-10-30 04:00 · arXiv cs.CL
Scoring Explanations Without Reading Them: Structural Shortcuts in Automated-Interpretability Evaluation Data
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