Multi-Resolution Attribution from Adaptive Routing State
Read the original on arXiv AI →The paper demonstrates that the routing state accumulated by adaptive hierarchical systems inherently provides a coherent attribution across the hierarchy. A leaf node’s contribution is the product of local routing weights along its path, while an internal node receives the corresponding prefix product, ensuring that finer readouts sum exactly to coarser ones. This attribution reflects the router’s learned preferences rather than intrinsic component values, and is shown to reveal meaningful structure at multiple levels in LLM, Census, agentic, and telecom-network hierarchies, with higher‑level readouts often offering clearer organization than leaf‑level ones.
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