arXiv Artificial Intelligence

Multi-Resolution Attribution from Adaptive Routing State

Multi-Resolution Attribution from Adaptive Routing State

Quick summary

arXiv:2605.22866v2 Announce Type: replace Abstract: Adaptive hierarchical systems accumulate routing state as they learn which components to select. We show that this state already defines a coherent attribution over the hierarchy. A leaf receives the product of the local routing weights on its path, while an internal node receives the corresponding prefix product. The same learned state can therefore be read consistently at group and component levels, and every finer readout sums exactly to its coarser counterpart. This attribution describes the preferences learned by the deployed router rath

Key takeaways

  • arXiv:2605.22866v2 Announce Type: replace Abstract: Adaptive hierarchical systems accumulate routing state as they learn which components to select.
  • We show that this state already defines a coherent attribution over the hierarchy.
  • A leaf receives the product of the local routing weights on its path, while an internal node receives the corresponding prefix product.

Why it matters

“Multi-Resolution Attribution from Adaptive Routing State” illustrates how changes in the AI ecosystem can affect products, workflows and user expectations together. Its lasting significance depends on measurable adoption, cost and safety outcomes.

Kaynak sitede devamını oku: arXiv Artificial Intelligence ↗