Quantifying Privacy Risks of Prompts in Visual Prompt Learning

Quantifying Privacy Risks of Prompts in Visual Prompt Learning

18 October 2023

Michael Backes

Mathias Humbert

Papers citing "Quantifying Privacy Risks of Prompts in Visual Prompt Learning"

6 / 6 papers shown

Title
DP-GPL: Differentially Private Graph Prompt Learning Jing Xu Franziska Boenisch Iyiola Emmanuel Olatunji Adam Dziedzic AAML 45 0 0 13 Mar 2025
PROMPTFUZZ: Harnessing Fuzzing Techniques for Robust Testing of Prompt Injection in LLMs Jiahao Yu Yangguang Shao Hanwen Miao Junzheng Shi SILM AAML 60 3 0 23 Sep 2024
Diversity-Aware Meta Visual Prompting Qidong Huang Xiaoyi Dong Dongdong Chen Weiming Zhang Feifei Wang Gang Hua Neng H. Yu VLM VPVLM 36 52 0 14 Mar 2023
M^4I: Multi-modal Models Membership Inference Pingyi Hu Zihan Wang Ruoxi Sun Hu Wang Minhui Xue 29 25 0 15 Sep 2022
The Power of Scale for Parameter-Efficient Prompt Tuning Brian Lester Rami Al-Rfou Noah Constant VPVLM 278 3,784 0 18 Apr 2021
Systematic Evaluation of Privacy Risks of Machine Learning Models Liwei Song Prateek Mittal MIACV 171 283 0 24 Mar 2020