Risk-Controlled Evidence Selection for Retrieval-Augmented Question Answering

Evidence compression must account for both shared context and the reader's dependence on the removed text. A low-cost solution to a predicted support graph need not preserve an answer. We separate these questions through shared-resource selection and calibration of the complete compression-and-fallback policy. The selector retains the classical additive covering guarantee while a validated flow relaxation supplies a separate, instance-specific bound on graph cost. A common budget-aware search addresses a further mismatch between penalized selection and hard admission budgets. This search preserves already-admitted contexts but must itself be included in calibration. Whole-policy calibration controls paired answer degradation among admitted questions, not absolute factual correctness. On 120 controlled graphs, safeguarded shared-cost selection reduces mean cost by 18.5% relative to additive greedy. Its graph-cost certificates have median ratio 1.132 and maximum 2.076, with no zero lower bounds in this family. A budget-repair study covers 2,400 paired selector configurations and retains a case where finite search misses a feasible budget. Simulations over 1,500 calibration samples quantify the cost of fallback. These studies establish optimization and statistical properties.