Anchored Privacy Drifting (APD) replaces privacy-sensitive visual elements with semantically equivalent alternatives while anchoring context, evaluated on the new AdaptShield benchmark with reported gains of 10.4% and 8.5% across four MLLM families.
Pii-visbench: Evalu- ating personally identifiable information safety in vision language models along a continuum of visibility.arXiv preprint arXiv:2601.05739, 2026
2 Pith papers cite this work. Polarity classification is still indexing.
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Introduces SopriBench benchmark and Argus agentic framework for user-level multimodal privacy leakage inference, reporting 0.55 PES with 25% improvement over baselines.
citing papers explorer
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Seeing Without Exposing: Adaptive Privacy Control for Open-World, Context-Hungry MLLMs
Anchored Privacy Drifting (APD) replaces privacy-sensitive visual elements with semantically equivalent alternatives while anchoring context, evaluated on the new AdaptShield benchmark with reported gains of 10.4% and 8.5% across four MLLM families.
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What Your Posts Reveal: A Benchmark and Agentic Framework for User-Level Privacy Leakage on Social Media
Introduces SopriBench benchmark and Argus agentic framework for user-level multimodal privacy leakage inference, reporting 0.55 PES with 25% improvement over baselines.