55 citations · 63 across the 11 of their papers we have counts for
6 papers · 1 filter
A Case for Computing on Unstructured Data
Mushtari Sadia, Amrita Roy Chowdhury, Ang Chen
Unstructured data, such as text, images, audio, and video, comprises the vast majority of the world's information, yet it remains poorly supported by traditional data systems that…
Piquant: Private Quantile Estimation in the Two-Server Model
Hannah Keller, Jacob Imola, Fabrizio Boninsegna +2
Quantiles are key in distributed analytics, but computing them over sensitive data risks privacy. Local differential privacy (LDP) offers strong protection but lower accuracy than…
What Really is a Member? Discrediting Membership Inference via Poisoning
Neal Mangaokar, Ashish Hooda, Zhuohang Li +5
Membership inference tests aim to determine whether a particular data point was included in a language model's training set. However, recent works have shown that such tests often…
SQUiD: Synthesizing Relational Databases from Unstructured Text
Mushtari Sadia, Zhenning Yang, Yunming Xiao +2
Relational databases are central to modern data management, yet most data exists in unstructured forms like text documents. To bridge this gap, we leverage large language models (L…
Differentially Private Quantiles with Smaller Error
Jacob Imola, Fabrizio Boninsegna, Hannah Keller +3
In the approximate quantiles problem, the goal is to output quantile estimates, the ranks of which are as close as possible to given quantiles $0 \leq q_1 \leq\dots \leq q_…
Prmpt: Sanitizing Sensitive Prompts for LLMs
Amrita Roy Chowdhury, David Glukhov, Divyam Anshumaan +4
The rise of large language models (LLMs) has introduced new privacy challenges, particularly during inference where sensitive information in prompts may be exposed to proprietary L…