most citedInitial Exploration of Zero-Shot Privacy Utility Tradeoffs in Tabular Data Using GPT-4

2 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CR2026

Picture the Epsilon: Pursuing Identity-Level Privacy Guarantees for Images

Arman Zareian Jahromi, Vishnu Bondalakunta, Mohammad Akbar Bin Shah +3

Several methods for auditing privacy in embedding spaces report a number called "epsilon." The common name is misleading: one number may be a heuristic score, another may come from…

cs.CR2026

Toward Interpretable Privacy Guarantees in Face-Swapping Anonymization

Vishnu Bondalakunta, Arman Zareian Jahromi, Shuangqing Wei +1

Face-swapping has emerged as a promising approach to facial privacy protection, replacing a target individual's appearance with that of a donor while preserving non-facial context.…

stat.ML2026

Mutual Information Collapse Explains Disentanglement Failure in -VAEs

Minh Vu, Xiaoliang Wan, Shuangqing Wei

The -VAE is a foundational framework for unsupervised disentanglement, using to regulate the trade-off between latent factorization and reconstruction fidelity. Empirically,…

cs.LG2024★ 2 cited

Initial Exploration of Zero-Shot Privacy Utility Tradeoffs in Tabular Data Using GPT-4

Bishwas Mandal, George Amariucai, Shuangqing Wei

We investigate the application of large language models (LLMs), specifically GPT-4, to scenarios involving the tradeoff between privacy and utility in tabular data. Our approach en…

cs.LG2024

Optimizing Privacy and Utility Tradeoffs for Group Interests Through Harmonization

Bishwas Mandal, George Amariucai, Shuangqing Wei

We propose a novel problem formulation to address the privacy-utility tradeoff, specifically when dealing with two distinct user groups characterized by unique sets of private and…