2 citations · 4 across the 9 of their papers we have counts for
4 papers · 1 filter
Adaptively Private Next-Token Prediction of Large Language Models
James Flemings, Meisam Razaviyayn, Murali Annavaram
As Large Language Models (LLMs) proliferate, developing privacy safeguards for these models is crucial. One popular safeguard involves training LLMs in a differentially private man…
Estimating Privacy Leakage of Augmented Contextual Knowledge in Language Models
James Flemings, Bo Jiang, Wanrong Zhang +2
Language models (LMs) rely on their parametric knowledge augmented with relevant contextual knowledge for certain tasks, such as question answering. However, the contextual knowled…
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…
Differentially Private Knowledge Distillation via Synthetic Text Generation
James Flemings, Murali Annavaram
Large Language models (LLMs) are achieving state-of-the-art performance in many different downstream tasks. However, the increasing urgency of data privacy puts pressure on practit…