5 papers
Secret-Protected Evolution for Differentially Private Synthetic Text Generation
Tianze Wang, Zhaoyu Chen, Jian Du +3
Text data has become extremely valuable on large language models (LLMs) and even lead to general artificial intelligence (AGI). A lot of high-quality text in the real world is priv…
TokenShapley: Token Level Context Attribution with Shapley Value
Yingtai Xiao, Yuqing Zhu, Sirat Samyoun +3
Large language models (LLMs) demonstrate strong capabilities in in-context learning, but verifying the correctness of their generated responses remains a challenge. Prior work has…
PrivacyGo: Privacy-Preserving Ad Measurement with Multidimensional Intersection
Jian Du, Haohao Qian, Shikun Zhang +6
This paper tackles the challenging and practical problem of multi-identifier private user profile matching for privacy-preserving ad measurement, a cornerstone of modern advertisin…
When Focus Enhances Utility: Target Range LDP Frequency Estimation and Unknown Item Discovery
Bo Jiang, Wanrong Zhang, Donghang Lu +2
Local Differential Privacy (LDP) protocols enable the collection of randomized client messages for data analysis, without the necessity of a trusted data curator. Such protocols ha…
Meeting Utility Constraints in Differential Privacy: A Privacy-Boosting Approach
Bo Jiang, Wanrong Zhang, Donghang Lu +3
Data engineering often requires accuracy (utility) constraints on results, posing significant challenges in designing differentially private (DP) mechanisms, particularly under str…