Aggregate Grounding Scores Hide Citation Turnover

Grounding benchmarks typically score whether a citation agrees with the benchmark’s evidence annotation under a single presentation. Such marginal scores do not reveal whether the same annotation-correct citations remain correct under content-preserving re-presentation: losses on some questions can be offset by gains on others, leaving aggregate quality nearly unchanged. We formalize this as an identification problem and introduce the Paired Citation Retention Audit (PCRA), which pairs each question’s citation outcome across presentations while holding the reader and available evidence fixed. On 3,330 NExT-GQA questions, two 8B video readers lose 24.2% and 42.0% of their initially correct temporal citations under reordering, corresponding to 3.82% and 5.78% of all question–order pairs, while net hit-rate changes remain near zero. The loss is far larger than under identical-input repeats and minimal perturbation controls, and it persists under exhaustive order coverage and across reader families, packet providers, and model scales. The same pattern appears in text RAG, where six HotpotQA readers lose 4.0–12.6% of their initially correct paragraph citations. Presentation variation also affects reader comparison. On small labelled video sets, averaging grounding quality across multiple presentations improves ranking reliability, whereas paired retention measures whether previously correct grounding decisions are preserved across presentations. The two therefore serve complementary roles: presentation-averaged quality stabilizes reader comparison, whereas PCRA exposes citation turnover that marginal scores cannot identify.