Risk-Controlled Applicability Set Retrieval for Regulation-Grounded Construction-Site Visual Screening

Screening construction-site photographs against safety regulations requires two decisions: which provisions apply to what is visible, and whether each is met. Passing a fixed number of relevance-ranked provisions to a judging model misses many recorded violations; widening the list causes false alarms on inapplicable provisions. We propose Risk-Controlled Applicability Set Retrieval (RCASR), which selects provisions to check from image evidence that each provision’s subject and hazardous state are visible, at a stated review budget or miss risk. On 346 photographs from 48 sites, with site-grouped cross-fitting and baselines at equal candidate counts, RCASR raised the share of recorded violations retrieved at three candidates per image from 0.515 for a lexical baseline (BM25) to 0.709. At two candidates per image it kept that baseline’s three-candidate recall after judgment and cut false alarms per image from 1.28 to 1.00. Holding the miss risk at 10% with conformal risk control required about ten candidates per image. The gains held for behaviour, housekeeping and edge provisions but not openings; on a public dataset, detection rose for two of four rules and fell for a machinery-proximity rule. The method runs on a quadruped patrol robot; its unlabelled field frames show deployment feasibility, not field accuracy.