Auditing Neural Thickets with Low-Rank Routes

Neural thickets suggest that many task experts may lie dense around pretrained weights, but density does not mean those experts are easy to discover. This audit tests whether nearby experts can be found through tiny learned low-rank routes under deployable selection and matched total query budgets, producing a mixed but useful probe of selector-sensitive neighborhoods. Accepted to the ICML 2026…