Reverse-engineering neural networks into understandable algorithms and circuit diagrams.
Chris Olah
Polysemanticity—where individual neurons activate on multiple unrelated concepts—has long impeded mechanistic interpretability. We apply sparse autoencoders to intermediate activat...
Lee Sharkey
We train sparse autoencoders on the activations of large language models and show that they extract thousands of human-interpretable features. These features decompose complex supe...
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