Inicio
Explorar
nav.journalClub
Tendencias
Más
synapse
⌘+K
Idioma
Español
Español
March 3, 2026
Quantifying observable privacy in differentially private generative models under black-box access
YG
Yinchi Ge
HZ
Hui Zhang
HS
Haohang Sun
Ver todo
Puntos clave
The outcome reveals a method to quantify observable privacy in these models, enhancing data utility.
Key evidence shows that differential privacy mechanisms significantly influence privacy levels.
Approach involves assessing various generative models under black-box access to evaluate privacy risks.
Significance suggests a need for better privacy management in AI systems using generative models.
Mark Helpful
Me gusta
Save
Guardar
Relay
Compartir
Mark Helpful
Me gusta
Save
Guardar
Relay
Compartir
Quantifying observable privacy in differentially private generative models under black-box access | Synapse
Cite This Study
Copy
Ge et al. (Fri,) studied this question.
synapsesocial.com/papers/69a75f9bc6e9836116a2b189
https://doi.org/https://doi.org/10.1016/j.neucom.2026.132893