M. Kantarcioglu

Protecting Sensitive Data in Image Synthesis via PAC-Private Adaptation for Diffusion Models

Synthetic data are increasingly used as an alternative to sharing sensitive records. However, synthetic data generation does not guarantee privacy, as diffusion models trained or adapted on sensitive data remain susceptible to reconstruction attacks. Moreover, while approaches that use differential privacy (DP), such a...

CARE-MVLM: Counterfactual Abstention and Region-Grounded Evidence in Mammography Vision-Language Models

Accuracy Overstates Evidence Grounding and Abstention Reliability in Mammography Vision-Language Models

An evidence-grounded selective evaluation benchmark that evaluates Pathology classification and Abnormality identification together with label-aware lesion localization suggests that answer accuracy and abstention behavior can substantially overstate the reliability of current VLM when predictions are not verified agai...