4 papers
InvisibleInk: High-Utility and Low-Cost Text Generation with Differential Privacy
Vishnu Vinod, Krishna Pillutla, Abhradeep Guha Thakurta
As major progress in LLM-based long-form text generation enables paradigms such as retrieval-augmented generation (RAG) and inference-time scaling, safely incorporating private inf…
Language Models can Subtly Deceive Without Lying: A Case Study on Strategic Phrasing in Legislation
Atharvan Dogra, Krishna Pillutla, Ameet Deshpande +5
We explore the ability of large language models (LLMs) to engage in subtle deception through strategically phrasing and intentionally manipulating information. This harmful behavio…
Correlated Noise Mechanisms for Differentially Private Learning
Krishna Pillutla, Jalaj Upadhyay, Christopher A. Choquette-Choo +9
This monograph explores the design and analysis of correlated noise mechanisms for differential privacy (DP), focusing on their application to private training of AI and machine le…
An Inversion Theorem for Buffered Linear Toeplitz (BLT) Matrices and Applications to Streaming Differential Privacy
H. Brendan McMahan, Krishna Pillutla
Buffered Linear Toeplitz (BLT) matrices are a family of parameterized lower-triangular matrices that play an important role in streaming differential privacy with correlated noise.…