When Models Don't Manipulate Manifolds: The Geometry of a Comparison Task.

arXiv:2609.37680v1 Announce Type: cross Abstract: One of the current premises of mechanistic interpretability research is that detailed accounts of the geometry of neural network representations can tell us how models perform computations, and how to effective