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MultimodalCoViP2609.04801

Whose record is this? Diagnosing and authorizing record use in personalized multimodal models

Xinyu Mao, Junsi Li, Chenyang Liu, Haoji Zhang, Ming Sun

cs.AI

Abstract

Contextualized visual personalization can retrieve a true record yet apply it to the wrong visual subject. We formalize when a record may condition an answer as \emph{record authorization}: subject presence (P), record-edge validity (E), and answer support (S) must all hold. We call violations visual memory misbinding (VMM). We construct RecordAuth-Diag, a 3,690-case matched diagnostic suite that changes one image--record edge while holding the query, question, record text, and image multiset fixed. Card removal and nonce relabeling attribute these failures to supplied records. Raw-bank failures span Qwen-, Phi-, and Gemma-family interfaces: Gemma-3-4B-IT reaches 63.69\% local unauthorized use at 25.75\% clean recall. CoViP remains at 26.02\%, versus 22.49\% for its Qwen backbone at similar clean recall. Typed pre-generation authorization reduces Qwen card exposure on RecordAuth-Diag from 43.63\% to 3.06\%, while positive recall changes from 86.26\% to 60.90\%. Full $P\wedge E\wedge S$ validation uses 560 localized DAVIS cases: top-1 relevance and typed authorization have comparable release (28.93\% and 28.39\%) but 6.79\% and 0.89\% unsafe release, respectively. Of the 33 additional unsafe cases removed, 27 are support, 4 edge, 2 clean, and 0 boundary cases. Thus the observed increment is an $E\wedge S$ decision dominated by support, not an edge check alone. Appearance supplies E evidence only conditional on P; authenticated subject tokens instantiate the missing presence witness as a sufficiency control. The claims concern the evaluated contracts, not natural prevalence, consent, or visual identity

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