2 citations · 4 across the 9 of their papers we have counts for
4 papers · 1 filter
PrivacySIM: Evaluating LLM Simulation of User Privacy Behavior
James Flemings, Murali Annavaram
Large language models (LLMs) are increasingly used to simulate human behavior, but their ability to simulate privacy decisions is not well understood. In this paper, w…
Differentially Private Retrieval-Augmented Generation
Tingting Tang, James Flemings, Yongqin Wang +1
Retrieval-augmented generation (RAG) is a widely used framework for reducing hallucinations in large language models (LLMs) on domain-specific tasks by retrieving relevant document…
Personalizing Agent Privacy Decisions via Logical Entailment
James Flemings, Ren Yi, Octavian Suciu +3
Personal large language model (LLM) agents increasingly perform tasks that require access to user data, raising concerns about appropriate data disclosure. We show that relying sol…
Differentially Private Next-Token Prediction of Large Language Models
James Flemings, Meisam Razaviyayn, Murali Annavaram
Ensuring the privacy of Large Language Models (LLMs) is becoming increasingly important. The most widely adopted technique to accomplish this is DP-SGD, which trains a model to gua…