15 citations · 48 across the 32 of their papers we have counts for
5 papers · 1 filter
Breaking Distortion-free Watermarks in Large Language Models
Shayleen Reynolds, Hengzhi He, Dung Daniel T. Ngo +5
In recent years, LLM watermarking has emerged as an attractive safeguard against AI-generated content, with promising applications in many real-world domains. However, there are gr…
Adaptive and Robust Watermark for Generative Tabular Data
Dung Daniel Ngo, Archan Ray, Akshay Seshadri +6
In recent years, watermarking generative tabular data has become a prominent framework to protect against the misuse of synthetic data. However, while most prior work in watermarki…
Guarding Multiple Secrets: Enhanced Summary Statistic Privacy for Data Sharing
Shuaiqi Wang, Rongzhe Wei, Mohsen Ghassemi +2
Data sharing enables critical advances in many research areas and business applications, but it may lead to inadvertent disclosure of sensitive summary statistics (e.g., means or q…
Six Levels of Privacy: A Framework for Financial Synthetic Data
Tucker Balch, Vamsi K. Potluru, Deepak Paramanand +1
Synthetic Data is increasingly important in financial applications. In addition to the benefits it provides, such as improved financial modeling and better testing procedures, it p…
Differentially Private Synthetic Data Using KD-Trees
Eleonora Kreačić, Navid Nouri, Vamsi K. Potluru +2
Creation of a synthetic dataset that faithfully represents the data distribution and simultaneously preserves privacy is a major research challenge. Many space partitioning based a…