Privacy-Preserving In-Context Learning for Large Language Models

Privacy-Preserving In-Context Learning for Large Language Models

2 May 2023

Jiachen T. Wang

Papers citing "Privacy-Preserving In-Context Learning for Large Language Models"

10 / 10 papers shown

Title
Privacy-Preserving Federated Embedding Learning for Localized Retrieval-Augmented Generation Qianren Mao Qili Zhang Hanwen Hao Zhentao Han Runhua Xu ... Bo Li Y. Song Jin Dong Jianxin Li Philip S. Yu 63 0 0 27 Apr 2025
The Canary's Echo: Auditing Privacy Risks of LLM-Generated Synthetic Text Matthieu Meeus Lukas Wutschitz Santiago Zanella Béguelin Shruti Tople Reza Shokri 70 0 0 24 Feb 2025
On the Privacy Risk of In-context Learning Haonan Duan Adam Dziedzic Mohammad Yaghini Nicolas Papernot Franziska Boenisch SILM PILM 61 35 0 15 Nov 2024
Confidential Prompting: Protecting User Prompts from Cloud LLM Providers In Gim Caihua Li Lin Zhong 35 2 0 27 Sep 2024
Private Fine-tuning of Large Language Models with Zeroth-order Optimization Xinyu Tang Ashwinee Panda Milad Nasr Saeed Mahloujifar Prateek Mittal 42 18 0 09 Jan 2024
DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer Junyuan Hong Jiachen T. Wang Chenhui Zhang Zhangheng Li Bo-wen Li Zhangyang Wang 28 29 0 27 Nov 2023
A Joint Exponential Mechanism For Differentially Private Top- $k$ Jennifer Gillenwater Matthew Joseph Andrés Munoz Medina Mónica Ribero 86 14 0 28 Jan 2022
Differentially Private Fine-tuning of Language Models Da Yu Saurabh Naik A. Backurs Sivakanth Gopi Huseyin A. Inan ... Y. Lee Andre Manoel Lukas Wutschitz Sergey Yekhanin Huishuai Zhang 134 344 0 13 Oct 2021
Hyperparameter Tuning with Renyi Differential Privacy Nicolas Papernot Thomas Steinke 117 118 0 07 Oct 2021
NeMo: a toolkit for building AI applications using Neural Modules Oleksii Kuchaiev Jason Chun Lok Li Huyen Nguyen Oleksii Hrinchuk Ryan Leary ... Jack Cook P. Castonguay Mariya Popova Jocelyn Huang Jonathan M. Cohen 174 287 0 14 Sep 2019