2 papers
cs.LG2025
Differentially Private In-context Learning via Sampling Few-shot Mixed with Zero-shot Outputs
James Flemings, Haosheng Gan, Hongyi Li +2
In-context learning (ICL) has shown promising improvement in downstream task adaptation of LLMs by augmenting prompts with relevant input-output examples (demonstrations). However,…
cs.LG2024
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…