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Privacy-Preserving In-Context Learning with Differentially Private
  Few-Shot Generation

Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation

21 September 2023
Xinyu Tang
Richard Shin
Huseyin A. Inan
Andre Manoel
Fatemehsadat Mireshghallah
Zinan Lin
Sivakanth Gopi
Janardhan Kulkarni
Robert Sim
ArXivPDFHTML

Papers citing "Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation"

47 / 47 papers shown
Title
Privacy Risks and Preservation Methods in Explainable Artificial Intelligence: A Scoping Review
Privacy Risks and Preservation Methods in Explainable Artificial Intelligence: A Scoping Review
Sonal Allana
Mohan Kankanhalli
Rozita Dara
32
0
0
05 May 2025
A Framework for Situating Innovations, Opportunities, and Challenges in Advancing Vertical Systems with Large AI Models
A Framework for Situating Innovations, Opportunities, and Challenges in Advancing Vertical Systems with Large AI Models
Gaurav Verma
Jiawei Zhou
Mohit Chandra
Srijan Kumar
M. D. Choudhury
53
0
0
03 Apr 2025
DPImageBench: A Unified Benchmark for Differentially Private Image Synthesis
DPImageBench: A Unified Benchmark for Differentially Private Image Synthesis
Chen Gong
Kecen Li
Zinan Lin
Tianhao Wang
61
3
0
18 Mar 2025
Synthesizing Privacy-Preserving Text Data via Finetuning without Finetuning Billion-Scale LLMs
Synthesizing Privacy-Preserving Text Data via Finetuning without Finetuning Billion-Scale LLMs
Bowen Tan
Zheng Xu
Eric P. Xing
Zhiting Hu
Shanshan Wu
SyDa
87
0
0
16 Mar 2025
Privacy Auditing of Large Language Models
Ashwinee Panda
Xinyu Tang
Milad Nasr
Christopher A. Choquette-Choo
Prateek Mittal
PILM
62
5
0
09 Mar 2025
DP-GTR: Differentially Private Prompt Protection via Group Text Rewriting
Mingchen Li
Heng Fan
Song Fu
Junhua Ding
Yunhe Feng
43
0
0
06 Mar 2025
Transforming Tuberculosis Care: Optimizing Large Language Models For Enhanced Clinician-Patient Communication
Transforming Tuberculosis Care: Optimizing Large Language Models For Enhanced Clinician-Patient Communication
Daniil Filienko
Mahek Nizar
Javier Roberti
Denise Galdamez
Haroon Jakher
Sarah Iribarren
Weichao Yuwen
Martine De Cock
LM&MA
33
0
0
28 Feb 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
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
Mitigating the Privacy Issues in Retrieval-Augmented Generation (RAG) via Pure Synthetic Data
Mitigating the Privacy Issues in Retrieval-Augmented Generation (RAG) via Pure Synthetic Data
Shenglai Zeng
Jiankun Zhang
Pengfei He
J. Ren
Tianqi Zheng
Hanqing Lu
Han Xu
Hui Liu
Yue Xing
Jiliang Tang
146
9
0
21 Feb 2025
Private Text Generation by Seeding Large Language Model Prompts
Private Text Generation by Seeding Large Language Model Prompts
Supriya Nagesh
Justin Y. Chen
Nina Mishra
Tal Wagner
SyDa
SILM
62
1
0
20 Feb 2025
Open LLMs are Necessary for Current Private Adaptations and Outperform
  their Closed Alternatives
Open LLMs are Necessary for Current Private Adaptations and Outperform their Closed Alternatives
Vincent Hanke
Tom Blanchard
Franziska Boenisch
Iyiola Emmanuel Olatunji
Michael Backes
Adam Dziedzic
PILM
56
3
0
02 Nov 2024
Data-adaptive Differentially Private Prompt Synthesis for In-Context Learning
Data-adaptive Differentially Private Prompt Synthesis for In-Context Learning
Fengyu Gao
Ruida Zhou
T. Wang
Cong Shen
Jing Yang
37
2
0
15 Oct 2024
Bridging Today and the Future of Humanity: AI Safety in 2024 and Beyond
Bridging Today and the Future of Humanity: AI Safety in 2024 and Beyond
Shanshan Han
84
1
0
09 Oct 2024
Adaptively Private Next-Token Prediction of Large Language Models
Adaptively Private Next-Token Prediction of Large Language Models
James Flemings
Meisam Razaviyayn
Murali Annavaram
34
0
0
02 Oct 2024
Confidential Prompting: Protecting User Prompts from Cloud LLM Providers
Confidential Prompting: Protecting User Prompts from Cloud LLM Providers
In Gim
Caihua Li
Lin Zhong
47
2
0
27 Sep 2024
AI Delegates with a Dual Focus: Ensuring Privacy and Strategic
  Self-Disclosure
AI Delegates with a Dual Focus: Ensuring Privacy and Strategic Self-Disclosure
Xi Chen
Zhiyang Zhang
Fangkai Yang
Xiaoting Qin
Chao Du
...
Hangxin Liu
Qingwei Lin
Saravan Rajmohan
Dongmei Zhang
Qi Zhang
37
1
0
26 Sep 2024
NetDPSyn: Synthesizing Network Traces under Differential Privacy
NetDPSyn: Synthesizing Network Traces under Differential Privacy
Danyu Sun
Joann Qiongna Chen
Chen Gong
Tianhao Wang
Zhou Li
54
1
0
08 Sep 2024
Con-ReCall: Detecting Pre-training Data in LLMs via Contrastive Decoding
Con-ReCall: Detecting Pre-training Data in LLMs via Contrastive Decoding
Cheng Wang
Yiwei Wang
Bryan Hooi
Yujun Cai
Nanyun Peng
Kai-Wei Chang
42
2
0
05 Sep 2024
Membership Inference Attacks Against In-Context Learning
Membership Inference Attacks Against In-Context Learning
Rui Wen
Zehan Li
Michael Backes
Yang Zhang
39
6
0
02 Sep 2024
LLM-PBE: Assessing Data Privacy in Large Language Models
LLM-PBE: Assessing Data Privacy in Large Language Models
Qinbin Li
Junyuan Hong
Chulin Xie
Jeffrey Tan
Rachel Xin
...
Dan Hendrycks
Zhangyang Wang
Bo Li
Bingsheng He
Dawn Song
ELM
PILM
40
13
0
23 Aug 2024
Private prediction for large-scale synthetic text generation
Private prediction for large-scale synthetic text generation
Kareem Amin
Alex Bie
Weiwei Kong
Alexey Kurakin
Natalia Ponomareva
Umar Syed
Andreas Terzis
Sergei Vassilvitskii
SyDa
SILM
45
3
0
16 Jul 2024
ReCaLL: Membership Inference via Relative Conditional Log-Likelihoods
ReCaLL: Membership Inference via Relative Conditional Log-Likelihoods
Roy Xie
Junlin Wang
Ruomin Huang
Minxing Zhang
Rong Ge
Jian Pei
Neil Zhenqiang Gong
Bhuwan Dhingra
MIALM
45
11
0
23 Jun 2024
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
Lynn Chua
Badih Ghazi
Yangsibo Huang
Pritish Kamath
Ravi Kumar
Daogao Liu
Pasin Manurangsi
Amer Sinha
Chiyuan Zhang
29
11
0
20 Jun 2024
The Fire Thief Is Also the Keeper: Balancing Usability and Privacy in
  Prompts
The Fire Thief Is Also the Keeper: Balancing Usability and Privacy in Prompts
Zhili Shen
Zihang Xi
Ying He
Wei Tong
Jingyu Hua
Sheng Zhong
SILM
48
7
0
20 Jun 2024
Deconstructing The Ethics of Large Language Models from Long-standing
  Issues to New-emerging Dilemmas
Deconstructing The Ethics of Large Language Models from Long-standing Issues to New-emerging Dilemmas
Chengyuan Deng
Yiqun Duan
Xin Jin
Heng Chang
Yijun Tian
...
Kuofeng Gao
Sihong He
Jun Zhuang
Lu Cheng
Haohan Wang
AILaw
43
16
0
08 Jun 2024
PrE-Text: Training Language Models on Private Federated Data in the Age
  of LLMs
PrE-Text: Training Language Models on Private Federated Data in the Age of LLMs
Charlie Hou
Akshat Shrivastava
Hongyuan Zhan
Rylan Conway
Trang Le
Adithya Sagar
Giulia Fanti
Daniel Lazar
36
8
0
05 Jun 2024
Privacy Preserving Prompt Engineering: A Survey
Privacy Preserving Prompt Engineering: A Survey
Kennedy Edemacu
Xintao Wu
47
18
0
09 Apr 2024
DP-TabICL: In-Context Learning with Differentially Private Tabular Data
DP-TabICL: In-Context Learning with Differentially Private Tabular Data
Alycia N. Carey
Karuna Bhaila
Kennedy Edemacu
Xintao Wu
35
7
0
08 Mar 2024
Privacy-Preserving Instructions for Aligning Large Language Models
Privacy-Preserving Instructions for Aligning Large Language Models
Da Yu
Peter Kairouz
Sewoong Oh
Zheng Xu
34
17
0
21 Feb 2024
Privacy Profiles for Private Selection
Privacy Profiles for Private Selection
Antti Koskela
Rachel Redberg
Yu-Xiang Wang
34
1
0
09 Feb 2024
Private Fine-tuning of Large Language Models with Zeroth-order Optimization
Private Fine-tuning of Large Language Models with Zeroth-order Optimization
Xinyu Tang
Ashwinee Panda
Milad Nasr
Saeed Mahloujifar
Prateek Mittal
47
18
0
09 Jan 2024
DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt
  Engineer
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
48
29
0
27 Nov 2023
How Well Do Large Language Models Truly Ground?
How Well Do Large Language Models Truly Ground?
Hyunji Lee
Se June Joo
Chaeeun Kim
Joel Jang
Doyoung Kim
Kyoung-Woon On
Minjoon Seo
HILM
33
6
0
15 Nov 2023
Can LLMs Keep a Secret? Testing Privacy Implications of Language Models
  via Contextual Integrity Theory
Can LLMs Keep a Secret? Testing Privacy Implications of Language Models via Contextual Integrity Theory
Niloofar Mireshghallah
Hyunwoo J. Kim
Xuhui Zhou
Yulia Tsvetkov
Maarten Sap
Reza Shokri
Yejin Choi
PILM
35
75
0
27 Oct 2023
InferDPT: Privacy-Preserving Inference for Black-box Large Language
  Model
InferDPT: Privacy-Preserving Inference for Black-box Large Language Model
Meng Tong
Kejiang Chen
Jie Zhang
Yuang Qi
Weiming Zhang
Neng H. Yu
Tianwei Zhang
Zhikun Zhang
SILM
30
2
0
18 Oct 2023
Last One Standing: A Comparative Analysis of Security and Privacy of
  Soft Prompt Tuning, LoRA, and In-Context Learning
Last One Standing: A Comparative Analysis of Security and Privacy of Soft Prompt Tuning, LoRA, and In-Context Learning
Rui Wen
Tianhao Wang
Michael Backes
Yang Zhang
Ahmed Salem
AAML
21
10
0
17 Oct 2023
DPZero: Private Fine-Tuning of Language Models without Backpropagation
DPZero: Private Fine-Tuning of Language Models without Backpropagation
Liang Zhang
Bingcong Li
K. K. Thekumparampil
Sewoong Oh
Niao He
28
11
0
14 Oct 2023
Identifying and Mitigating Privacy Risks Stemming from Language Models:
  A Survey
Identifying and Mitigating Privacy Risks Stemming from Language Models: A Survey
Victoria Smith
Ali Shahin Shamsabadi
Carolyn Ashurst
Adrian Weller
PILM
32
24
0
27 Sep 2023
Differentially Private Synthetic Data via Foundation Model APIs 1: Images
Differentially Private Synthetic Data via Foundation Model APIs 1: Images
Zinan Lin
Sivakanth Gopi
Janardhan Kulkarni
Harsha Nori
Sergey Yekhanin
41
36
0
24 May 2023
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
Differentially Private Natural Language Models: Recent Advances and
  Future Directions
Differentially Private Natural Language Models: Recent Advances and Future Directions
Lijie Hu
Ivan Habernal
Lei Shen
Di Wang
AAML
30
18
0
22 Jan 2023
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
Jason W. Wei
Xuezhi Wang
Dale Schuurmans
Maarten Bosma
Brian Ichter
F. Xia
Ed H. Chi
Quoc Le
Denny Zhou
LM&Ro
LRM
AI4CE
ReLM
386
8,495
0
28 Jan 2022
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
TEM: High Utility Metric Differential Privacy on Text
TEM: High Utility Metric Differential Privacy on Text
Ricardo Silva Carvalho
Theodore Vasiloudis
Oluwaseyi Feyisetan
39
36
0
16 Jul 2021
Permute-and-Flip: A new mechanism for differentially private selection
Permute-and-Flip: A new mechanism for differentially private selection
Ryan McKenna
Daniel Sheldon
112
47
0
23 Oct 2020
BERT-of-Theseus: Compressing BERT by Progressive Module Replacing
BERT-of-Theseus: Compressing BERT by Progressive Module Replacing
Canwen Xu
Wangchunshu Zhou
Tao Ge
Furu Wei
Ming Zhou
221
197
0
07 Feb 2020
1