Skip to main content
Ryan Orban

Ryan Orban

Subject
4 entries

Mechanistic Interpretability

Bookmarks

  1. Neuronpedia Gemma Scope: interactive mechanistic interpretability for Gemma 2

    Neuronpedia's Gemma Scope microscope lets you scan Gemma 2's internal features using Sparse Autoencoders — activating features, steering behavior, browsing SAE decompositions. Interactive mechanistic interpretability for a production model.

  2. Linear Representations and Superposition in LLMs

    A clear explainer on how LLMs encode thousands of features in relatively small embedding spaces via superposition — the Johnson-Lindenstrauss lemma applied to neural representations. Good primer on the theoretical foundations behind SAE-based interpretability.

  3. ARENA Chapter 1.3.1: Toy Models of Superposition and SAEs

    ARENA Chapter 1.3.1: an interactive curriculum chapter on Toy Models of Superposition and Sparse Autoencoders — building from the theoretical model to hands-on SAE implementation. Part of the ARENA AI safety education program.

  4. Activation Steering Notebook (concentration_notebooks)

    A Jupyter notebook exploring activation steering in neural networks from the concentration_notebooks repo. Saved as a reference in the mechanistic interpretability and model steering space.

All bookmarks