Functorial Neural Architectures

Functorial Neural Architectures from Higher Inductive Types

arXiv:2603.16123v2 Announce Type: replace Abstract: Neural networks often learn the parts of a task but fail on novel combinations of those parts. We argue that this failure is architectural: a decoder generalizes compositionally only when it respects the algebraic laws of the task, i.e. when it descends from freely generated sequences to the quotient determined by those laws.