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Mind the Privacy Unit! User-Level Differential Privacy for Language
  Model Fine-Tuning

Mind the Privacy Unit! User-Level Differential Privacy for Language Model Fine-Tuning

20 June 2024
Lynn Chua
Badih Ghazi
Yangsibo Huang
Pritish Kamath
Ravi Kumar
Daogao Liu
Pasin Manurangsi
Amer Sinha
Chiyuan Zhang
ArXivPDFHTML

Papers citing "Mind the Privacy Unit! User-Level Differential Privacy for Language Model Fine-Tuning"

10 / 10 papers shown
Title
Protecting Users From Themselves: Safeguarding Contextual Privacy in Interactions with Conversational Agents
Protecting Users From Themselves: Safeguarding Contextual Privacy in Interactions with Conversational Agents
Ivoline Ngong
Swanand Kadhe
Hao Wang
K. Murugesan
Justin D. Weisz
Amit Dhurandhar
K. Ramamurthy
49
2
0
22 Feb 2025
A Hassle-free Algorithm for Private Learning in Practice: Don't Use Tree Aggregation, Use BLTs
A Hassle-free Algorithm for Private Learning in Practice: Don't Use Tree Aggregation, Use BLTs
H. B. McMahan
Zheng Xu
Yanxiang Zhang
FedML
37
5
0
16 Aug 2024
Fine-Tuning Large Language Models with User-Level Differential Privacy
Fine-Tuning Large Language Models with User-Level Differential Privacy
Zachary Charles
Arun Ganesh
Ryan McKenna
H. B. McMahan
Nicole Mitchell
Krishna Pillutla
Keith Rush
36
11
0
10 Jul 2024
Privacy-Preserving In-Context Learning for Large Language Models
Privacy-Preserving In-Context Learning for Large Language Models
Tong Wu
Ashwinee Panda
Jiachen T. Wang
Prateek Mittal
51
29
0
02 May 2023
Sparks of Artificial General Intelligence: Early experiments with GPT-4
Sparks of Artificial General Intelligence: Early experiments with GPT-4
Sébastien Bubeck
Varun Chandrasekaran
Ronen Eldan
J. Gehrke
Eric Horvitz
...
Scott M. Lundberg
Harsha Nori
Hamid Palangi
Marco Tulio Ribeiro
Yi Zhang
ELM
AI4MH
AI4CE
ALM
298
2,232
0
22 Mar 2023
How to DP-fy ML: A Practical Guide to Machine Learning with Differential
  Privacy
How to DP-fy ML: A Practical Guide to Machine Learning with Differential Privacy
Natalia Ponomareva
Hussein Hazimeh
Alexey Kurakin
Zheng Xu
Carson E. Denison
H. B. McMahan
Sergei Vassilvitskii
Steve Chien
Abhradeep Thakurta
94
167
0
01 Mar 2023
Differentially Private Fine-tuning of Language Models
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
347
0
13 Oct 2021
Practical and Private (Deep) Learning without Sampling or Shuffling
Practical and Private (Deep) Learning without Sampling or Shuffling
Peter Kairouz
Brendan McMahan
Shuang Song
Om Thakkar
Abhradeep Thakurta
Zheng Xu
FedML
182
154
0
26 Feb 2021
Extracting Training Data from Large Language Models
Extracting Training Data from Large Language Models
Nicholas Carlini
Florian Tramèr
Eric Wallace
Matthew Jagielski
Ariel Herbert-Voss
...
Tom B. Brown
D. Song
Ulfar Erlingsson
Alina Oprea
Colin Raffel
MLAU
SILM
290
1,815
0
14 Dec 2020
Scaling Laws for Neural Language Models
Scaling Laws for Neural Language Models
Jared Kaplan
Sam McCandlish
T. Henighan
Tom B. Brown
B. Chess
R. Child
Scott Gray
Alec Radford
Jeff Wu
Dario Amodei
258
4,489
0
23 Jan 2020
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