9 citations · 13 across the 10 of their papers we have counts for
11 papers
QuasiLeak-Bench: Evaluating LLM-Based Privacy Detectors on Policy-Conditioned Quasi-Evidence Group Recovery
Yufan Zhu, Yangfan Jiang, Yang Fei +3
Natural language messages often contain quasi-identifiers that are weak in isolation but can jointly reveal an individual's private attributes. We call such a jointly revealing set…
DriftXpress: Faster Drifting Models via Projected RKHS Fields
Ali Falahati, Elliot Creager, Gautam Kamath +1
Drifting Models have emerged as a new paradigm for one-step generative modeling, achieving strong image quality without iterative inference. The premise is to replace the iterative…
CAPID: Context-Aware PII Detection for Question-Answering Systems
Mariia Ponomarenko, Sepideh Abedini, Masoumeh Shafieinejad +3
Detecting personally identifiable information (PII) in user queries is critical for ensuring privacy in question-answering systems. Current approaches mainly redact all PII, disreg…
Rethinking Benchmarks for Differentially Private Image Classification
Sabrina Mokhtari, Sara Kodeiri, Shubhankar Mohapatra +2
We revisit benchmarks for differentially private image classification. We suggest a comprehensive set of benchmarks, allowing researchers to evaluate techniques for differentially…
MaskSQL: Safeguarding Privacy for LLM-Based Text-to-SQL via Abstraction
Sepideh Abedini, Shubhankar Mohapatra, D. B. Emerson +3
Large language models (LLMs) have shown promising performance on tasks that require reasoning, such as text-to-SQL, code generation, and debugging. However, regulatory frameworks w…
Computing Inconsistency Measures Under Differential Privacy
Shubhankar Mohapatra, Amir Gilad, Xi He +1
Assessing data quality is crucial to knowing whether and how to use the data for different purposes. Specifically, given a collection of integrity constraints, various ways have be…
Differentially Private Data Generation with Missing Data
Shubhankar Mohapatra, Jianqiao Zong, Florian Kerschbaum +1
Despite several works that succeed in generating synthetic data with differential privacy (DP) guarantees, they are inadequate for generating high-quality synthetic data when the i…
The Role of Adaptive Optimizers for Honest Private Hyperparameter Selection
Shubhankar Mohapatra, Sajin Sasy, Xi He +2
Hyperparameter optimization is a ubiquitous challenge in machine learning, and the performance of a trained model depends crucially upon their effective selection. While a rich set…
Kamino: Constraint-Aware Differentially Private Data Synthesis
Chang Ge, Shubhankar Mohapatra, Xi He +1
Organizations are increasingly relying on data to support decisions. When data contains private and sensitive information, the data owner often desires to publish a synthetic datab…
KryptoOracle: A Real-Time Cryptocurrency Price Prediction Platform Using Twitter Sentiments
Shubhankar Mohapatra, Nauman Ahmed, Paulo Alencar
Cryptocurrencies, such as Bitcoin, are becoming increasingly popular, having been widely used as an exchange medium in areas such as financial transaction and asset transfer verifi…
Triclustering of Gene Expression Microarray Data Using Coarse-Grained Parallel Genetic Algorithm
Shubhankar Mohapatra, Moumita Sarkar, Anjali Mohapatra +1
Microarray data analysis is one of the major area of research in the field computational biology. Numerous techniques like clustering, biclustering are often applied to microarray…