VStress: Correlation-Aware Auditing and Adaptive Budget Allocation for Repeated Verifiers

Repeated verifier calls are useful only when they contribute additional conditional information. We introduce VStress, an auditable replay contract, and VStress-CA, a correlation-aware allocation policy that estimates the conditional marginal information of an unqueried verifier on a sealed calibration split, discounts uncertainty, normalizes by call cost, and stops or abstains when the next query is not informative. The controller freezes its decision and cost ledger before accessing the clean oracle; a dependence-shift alarm disables channel preference and falls back to exact-stop. The controlled audit establishes the mechanism boundary: under 35% symmetric corruption, majority-5 improves balanced accuracy from 0.6578 to 0.7739, while at 65% corruption it decreases by 0.1226 points. In the fixed-budget comparison, breadth, redundancy, and adaptive allocation achieve balanced accuracies of 0.6048, 0.6375, and 0.6538, respectively, with VStress-CA reaching an RLVR score of 0.6417 using 3.4216 calls per item. Dependence diagnostics further show increasing conditional marginal gains when moving from same-model repeats to cross-family verifier channels, with gains of 0.0126, 0.0462, and 0.0913. These results transform verifier correlation from a post-hoc reliability concern into an auditable allocation signal for adaptive verification.