Learning Transfers: Kan Extensions for Neural Invariants

Excerpt

arXiv:2606.07627v3 Announce Type: replace Abstract: A representation transfers if it stays usable once the task has changed. Standard evaluations report target accuracy or a distance between data distributions, but neither says which structure of the representation is meant to survive. Here we make that structure explicit and computable. A task is a small category, a change of task is a functor, and a representation is a functor into a category of invariants. The structure the target has to exhi