Differentially Private Language Models Benefit from Public Pre-training

13 September 2020

Papers citing "Differentially Private Language Models Benefit from Public Pre-training"

38 / 38 papers shown

Title
NoEsis: Differentially Private Knowledge Transfer in Modular LLM Adaptation Rob Romijnders Stefanos Laskaridis Ali Shahin Shamsabadi Hamed Haddadi 57 0 0 25 Apr 2025
DP2Unlearning: An Efficient and Guaranteed Unlearning Framework for LLMs Tamim Al Mahmud N. Jebreel Josep Domingo-Ferrer David Sánchez MU 27 0 0 18 Apr 2025
Empirical Calibration and Metric Differential Privacy in Language Models Pedro Faustini Natasha Fernandes Annabelle McIver Mark Dras 60 0 0 18 Mar 2025
On the Impact of Noise in Differentially Private Text Rewriting Stephen Meisenbacher Maulik Chevli Florian Matthes 58 0 0 31 Jan 2025
Privately Learning from Graphs with Applications in Fine-tuning Large Language Models Haoteng Yin Rongzhe Wei Eli Chien P. Li 28 0 0 10 Oct 2024
Fine-Tuning Language Models with Differential Privacy through Adaptive Noise Allocation Xianzhi Li Ran Zmigrod Zhiqiang Ma Xiaomo Liu Xiaodan Zhu 9 1 0 03 Oct 2024
Undesirable Memorization in Large Language Models: A Survey Ali Satvaty Suzan Verberne Fatih Turkmen ELM PILM 71 7 0 03 Oct 2024
Thinking Outside of the Differential Privacy Box: A Case Study in Text Privatization with Language Model Prompting Stephen Meisenbacher Florian Matthes 18 2 0 01 Oct 2024
DP-MLM: Differentially Private Text Rewriting Using Masked Language Models Stephen Meisenbacher Maulik Chevli Juraj Vladika Florian Matthes 39 7 0 30 Jun 2024
IDT: Dual-Task Adversarial Attacks for Privacy Protection Pedro Faustini Shakila Mahjabin Tonni Annabelle McIver Qiongkai Xu Mark Dras SILM AAML 44 0 0 28 Jun 2024
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 26 8 0 05 Jun 2024
Advances in Differential Privacy and Differentially Private Machine Learning Saswat Das Subhankar Mishra 22 3 0 06 Apr 2024
LLM-based Privacy Data Augmentation Guided by Knowledge Distillation with a Distribution Tutor for Medical Text Classification Yiping Song Juhua Zhang Zhiliang Tian Yuxin Yang Minlie Huang Dongsheng Li 34 10 0 26 Feb 2024
ConfusionPrompt: Practical Private Inference for Online Large Language Models Peihua Mai Ran Yan Rui Ye Youjia Yang Yinchuan Li Yan Pang 15 1 0 30 Dec 2023
Locally Differentially Private Document Generation Using Zero Shot Prompting Saiteja Utpala Sara Hooker Pin-Yu Chen 13 36 0 24 Oct 2023
Split-and-Denoise: Protect large language model inference with local differential privacy Peihua Mai Ran Yan Zhe Huang Youjia Yang Yan Pang 27 10 0 13 Oct 2023
LatticeGen: A Cooperative Framework which Hides Generated Text in a Lattice for Privacy-Aware Generation on Cloud Mengke Zhang Tianxing He Tianle Wang Lu Mi Fatemehsadat Mireshghallah Binyi Chen Hao Wang Yulia Tsvetkov 32 0 0 29 Sep 2023
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
Differential Privacy, Linguistic Fairness, and Training Data Influence: Impossibility and Possibility Theorems for Multilingual Language Models Phillip Rust Anders Søgaard 25 3 0 17 Aug 2023
Selective Pre-training for Private Fine-tuning Da Yu Sivakanth Gopi Janardhan Kulkarni Zi-Han Lin Saurabh Naik Tomasz Religa Jian Yin Huishuai Zhang 30 19 0 23 May 2023
Can Public Large Language Models Help Private Cross-device Federated Learning? Boxin Wang Yibo Zhang Yuan Cao Bo-wen Li H. B. McMahan Sewoong Oh Zheng Xu Manzil Zaheer FedML 21 37 0 20 May 2023
Privacy-Preserving Prompt Tuning for Large Language Model Services Yansong Li Zhixing Tan Yang Liu SILM VLM 45 63 0 10 May 2023
Why Is Public Pretraining Necessary for Private Model Training? Arun Ganesh Mahdi Haghifam Milad Nasr Sewoong Oh Thomas Steinke Om Thakkar Abhradeep Thakurta Lun Wang 16 36 0 19 Feb 2023
Efficiency 360: Efficient Vision Transformers Badri N. Patro Vijay Srinivas Agneeswaran 21 6 0 16 Feb 2023
Context-Aware Differential Privacy for Language Modeling M. H. Dinh Ferdinando Fioretto 23 2 0 28 Jan 2023
Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping Jiyan He Xuechen Li Da Yu Huishuai Zhang Janardhan Kulkarni Y. Lee A. Backurs Nenghai Yu Jiang Bian 14 46 0 03 Dec 2022
Language Generation Models Can Cause Harm: So What Can We Do About It? An Actionable Survey Sachin Kumar Vidhisha Balachandran Lucille Njoo Antonios Anastasopoulos Yulia Tsvetkov ELM 66 85 0 14 Oct 2022
THE-X: Privacy-Preserving Transformer Inference with Homomorphic Encryption Tianyu Chen Hangbo Bao Shaohan Huang Li Dong Binxing Jiao Daxin Jiang Haoyi Zhou Jianxin Li Furu Wei 15 96 0 01 Jun 2022
Can Foundation Models Help Us Achieve Perfect Secrecy? Simran Arora Christopher Ré FedML 11 6 0 27 May 2022
Sentence-level Privacy for Document Embeddings Casey Meehan Khalil Mrini Kamalika Chaudhuri 11 19 0 10 May 2022
The Impact of Differential Privacy on Group Disparity Mitigation Victor Petrén Bach Hansen A. Neerkaje Ramit Sawhney Lucie Flek Anders Søgaard 40 9 0 05 Mar 2022
Submix: Practical Private Prediction for Large-Scale Language Models Antonio A. Ginart L. V. D. van der Maaten James Y. Zou Chuan Guo 20 22 0 04 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 134 346 0 13 Oct 2021
Large Language Models Can Be Strong Differentially Private Learners Xuechen Li Florian Tramèr Percy Liang Tatsunori Hashimoto 22 365 0 12 Oct 2021
Learning Domain Specific Language Models for Automatic Speech Recognition through Machine Translation Saurav Jha 12 1 0 21 Sep 2021
Selective Differential Privacy for Language Modeling Weiyan Shi Aiqi Cui Evan Li R. Jia Zhou Yu 13 68 0 30 Aug 2021
DPlis: Boosting Utility of Differentially Private Deep Learning via Randomized Smoothing Wenxiao Wang Tianhao Wang Lun Wang Nanqing Luo Pan Zhou D. Song R. Jia 4 16 0 02 Mar 2021
KART: Parameterization of Privacy Leakage Scenarios from Pre-trained Language Models Yuta Nakamura S. Hanaoka Y. Nomura Naoto Hayashi O. Abe Shuntaro Yada Shoko Wakamiya Nara Institute of Science MIACV 16 8 0 31 Dec 2020