ArXiv TLDR

Sheridan Feucht

2 papers · Latest:

Machine Learning

Manifold Steering Reveals the Shared Geometry of Neural Network Representation and Behavior

This paper shows that neural network representation geometry causally shapes behavior, enabling principled control through "manifold steering."

2605.05115
Machine Learning

Do Sparse Autoencoders Capture Concept Manifolds?

This paper explores how Sparse Autoencoders (SAEs) capture concept manifolds, finding they often mix global and local solutions, leading to "dilution."

2604.28119

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