True Record, Wrong Subject: Diagnosing Visual Memory Misbinding in Personalized Multimodal Models

A personal record can be true without applying to the subject shown in a query. We study this visual memory misbinding through a controlled diagnosis of record applicability and stage-specific decisions. A record-level contract separates subject presence ($P$), image–record assignment ($E$), and answer support ($S$). RecordAuth-Diag contains 3,690 cases with matched assignment interventions and distinct support, presence, and ambiguity controls. Card removal and nonce relabeling establish dependence on supplied records among cases with unsafe outputs before authorization. On 560 localized DAVIS cases, an ATRA-based context guard increases correct record answers from 170 to 228 while reducing unsafe record use from 149 to 5. Filtering full-bank answers by the same retained event set preserves only 144 correct answers. Context selection therefore changes which record answers the generator produces, beyond withholding an existing answer. Retaining the correct target does not ensure that generation uses it, and exact field execution can expose an invalid selected association. A lower rate of unsafe record use in model outputs does not necessarily imply a less contaminated selected context. These interactions motivate a structured-query reference pipeline separating record selection, field execution, and candidate acceptance. Under unchanged checks, the post-hoc Field comparison yields more correct answers and more unsafe releases than checked MLLM readout. Code and reproducibility materials are available at https://anonymous.4open.science/r/visual-memory-misbinding-1E03.