AI RESEARCH
The Attribution Impossibility: No Feature Ranking Is Faithful, Stable, and Complete Under Collinearity
arXiv CS.AI
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ArXi:2605.21492v1 Announce Type: cross No feature ranking can be simultaneously faithful, stable, and complete when features are collinear. For collinear pairs, ranking reduces to a coin flip. We prove this impossibility, quantify it for four model classes, resolve it via ensemble averaging (DASH), and machine-verify it with 305 Lean 4 theorems.