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Many approximation methods enlarge a trial space by adjoining function blocks generated by different operators. Exact redundancy and strong cross-level interaction can make coefficients nonunique and render pairwise or diagonal-dominance tests needlessly pessimistic. For \(V_m=\sum_{\ell\leq m}S_\ell(E_\ell)\) in a Hil...
AI-workflow governance cannot be reduced to checking the final answer: an apparently safe answer may rest on a fragile evidence path that ordinary evaluation cannot see, localize or govern, so SSEG moves governance below surface-level output checking into auditable, path-specific decisions about intervention, revalidat...
The proposed map turns semantic uncertainty in generative systems into an identifiable and testable statistical measurement problem and, when its acceptance conditions hold, yields an auditable posterior estimate.
This work introduces Schur–Riesz refinement, a variational framework for combining ordinary polynomial finite-element refinement with functions derived from known PDE structure, thereby bridging width-optimal spaces and stable, computable adaptive approximation.
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