Multi-Resolution Attribution from Adaptive Routing State
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 rather than an intrinsic or counterfactual value of a component. Across LLM, Census, agentic, and telecom-network hierarchies, the learned state contains...
| Authors | Joss Armstrong |
|---|---|
| Primary category | cs.AI |
| Published | 19 May 2026 |
| Last updated at source | 17 September 2026 |
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