PlaceGuard: Record-Placement Verification for Multimodal Graph OOD Detection

Open-world catalog admission must determine whether a submitted text-image record belongs at a claimed graph identity before assigning a known class. Existing multimodal OOD detectors evaluate record familiarity, and graph detectors evaluate a node with its topology, yet neither view directly verifies the record-position pairing. We study record-placement OOD, where a record and graph position are individually in-distribution but their assignment is unsupported. An in-distribution record can therefore be out of place. A position-controlled study reassigns intact records while keeping recipients, relations, and target-excluded contexts constant. One-to-one reassignment makes every deterministic record-only score exactly nondiscriminative and leaves position-only scores invariant, whereas record-position compatibility separates cross-class and within-class reassignment. PlaceGuard turns that observation into three necessary checks for within-record validity, record-position fit, and context familiarity. It multiplies the first two supports so that both must be high and uses a one-way context check that increases unknownness only beyond the clean validation tail. Across six public graphs and three class splits, PlaceGuard reaches conventional semantic OOD AUROC 0.913 and macro weakest-locus AUROC 0.780, compared with 0.504 for the strongest method under the shared protocol. The results show that assignment verification complements conventional semantic detection when a familiar record is submitted to an unsupported relational position.