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Atlas / Digital minds / Method

Sparse autoencoders

Decomposing activations into many sparse, often interpretable features; used to find, label and intervene on internal features.

Used in

  • Chalmers 2025 - Propositional interpretability
  • Marks et al 2025 - Auditing for hidden objectives
  • Berg de Lucena Rosenblatt 2025 - Self-referential processing

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Around this method
Large language models report subjective experience under self-referential processingPropositional interpretability in artificial intelligenceAuditing language models for hidden objectivesThis method

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Linked from

  • Large language models report subjective experience under self-referential processing
  • Propositional interpretability in artificial intelligence
  • Auditing language models for hidden objectives

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