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Harnessing large-language models to generate private synthetic text

Harnessing large-language models to generate private synthetic text

2 June 2023
Alexey Kurakin
Natalia Ponomareva
Umar Syed
Liam MacDermed
Andreas Terzis
    SILM
    SyDa
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Papers citing "Harnessing large-language models to generate private synthetic text"

12 / 12 papers shown
Title
LLM Security: Vulnerabilities, Attacks, Defenses, and Countermeasures
LLM Security: Vulnerabilities, Attacks, Defenses, and Countermeasures
Francisco Aguilera-Martínez
Fernando Berzal
PILM
52
0
0
02 May 2025
A False Sense of Privacy: Evaluating Textual Data Sanitization Beyond Surface-level Privacy Leakage
A False Sense of Privacy: Evaluating Textual Data Sanitization Beyond Surface-level Privacy Leakage
Rui Xin
Niloofar Mireshghallah
Shuyue Stella Li
Michael Duan
Hyunwoo Kim
Yejin Choi
Yulia Tsvetkov
Sewoong Oh
Pang Wei Koh
74
1
0
28 Apr 2025
The Canary's Echo: Auditing Privacy Risks of LLM-Generated Synthetic Text
The Canary's Echo: Auditing Privacy Risks of LLM-Generated Synthetic Text
Matthieu Meeus
Lukas Wutschitz
Santiago Zanella Béguelin
Shruti Tople
Reza Shokri
80
0
0
24 Feb 2025
Bayesian Power Steering: An Effective Approach for Domain Adaptation of
  Diffusion Models
Bayesian Power Steering: An Effective Approach for Domain Adaptation of Diffusion Models
Ding Huang
Ting Li
Jian Huang
DiffM
39
1
0
06 Jun 2024
Privacy Preserving Prompt Engineering: A Survey
Privacy Preserving Prompt Engineering: A Survey
Kennedy Edemacu
Xintao Wu
39
18
0
09 Apr 2024
Synthetic Text Generation using Hypergraph Representations
Synthetic Text Generation using Hypergraph Representations
Natraj Raman
Sameena Shah
10
1
0
06 Sep 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
346
0
13 Oct 2021
Deduplicating Training Data Makes Language Models Better
Deduplicating Training Data Makes Language Models Better
Katherine Lee
Daphne Ippolito
A. Nystrom
Chiyuan Zhang
Douglas Eck
Chris Callison-Burch
Nicholas Carlini
SyDa
242
592
0
14 Jul 2021
The Power of Scale for Parameter-Efficient Prompt Tuning
The Power of Scale for Parameter-Efficient Prompt Tuning
Brian Lester
Rami Al-Rfou
Noah Constant
VPVLM
280
3,844
0
18 Apr 2021
The Pile: An 800GB Dataset of Diverse Text for Language Modeling
The Pile: An 800GB Dataset of Diverse Text for Language Modeling
Leo Gao
Stella Biderman
Sid Black
Laurence Golding
Travis Hoppe
...
Horace He
Anish Thite
Noa Nabeshima
Shawn Presser
Connor Leahy
AIMat
253
1,989
0
31 Dec 2020
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
1,814
0
14 Dec 2020
1