DP-Forward: Fine-tuning and Inference on Language Models with Differential Privacy in Forward Pass

13 September 2023

Papers citing "DP-Forward: Fine-tuning and Inference on Language Models with Differential Privacy in Forward Pass"

43 / 43 papers shown

Title
Cape: Context-Aware Prompt Perturbation Mechanism with Differential Privacy Haoqi Wu Wei Dai Li Wang Qiang Yan SILM 33 0 0 09 May 2025
OBLIVIATE: Robust and Practical Machine Unlearning for Large Language Models Xiaoyu Xu Minxin Du Qingqing Ye Haibo Hu MU 57 0 0 07 May 2025
Collaborative LLM Numerical Reasoning with Local Data Protection Min Zhang Yuzhe Lu Yun Zhou Panpan Xu Lin Lee Cheong Chang-Tien Lu Haozhu Wang 55 0 0 01 Apr 2025
Safeguarding LLM Embeddings in End-Cloud Collaboration via Entropy-Driven Perturbation Shuaifan Jin Xiaoyi Pang Zhibo Wang He Wang Jiacheng Du Jiahui Hu Kui Ren SILM AAML 78 0 0 17 Mar 2025
A General Pseudonymization Framework for Cloud-Based LLMs: Replacing Privacy Information in Controlled Text Generation Shilong Hou Ruilin Shang Zi Long Xianghua Fu Yin Chen 64 0 0 24 Feb 2025
DP-MemArc: Differential Privacy Transfer Learning for Memory Efficient Language Models Yanming Liu Xinyue Peng Yuwei Zhang Xiaolan Ke Songhang Deng ... Sheng Cheng Xun Wang Jianwei Yin Tianyu Du Xuhong Zhang 72 0 0 21 Feb 2025
Efficient and Private: Memorisation under differentially private parameter-efficient fine-tuning in language models Olivia Ma Jonathan Passerat-Palmbach Dmitrii Usynin 77 0 0 24 Nov 2024
A Practical and Privacy-Preserving Framework for Real-World Large Language Model Services Yu Mao Xueping Liao Wei Liu Anjia Yang 29 0 0 03 Nov 2024
On the Vulnerability of Text Sanitization Meng Tong Kejiang Chen Xiaojian Yuang J. Liu W. Zhang Nenghai Yu Jie Zhang 52 0 0 22 Oct 2024
Unveiling the Vulnerability of Private Fine-Tuning in Split-Based Frameworks for Large Language Models: A Bidirectionally Enhanced Attack Guanzhong Chen Zhenghan Qin Mingxin Yang Yajie Zhou Tao Fan Tianyu Du Zenglin Xu AAML 51 4 0 02 Sep 2024
Characterizing Stereotypical Bias from Privacy-preserving Pre-Training Stefan Arnold Rene Gröbner Annika Schreiner 37 0 0 30 Jun 2024
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 40 7 0 20 Jun 2024
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 40 16 0 08 Jun 2024
NAP^2: A Benchmark for Naturalness and Privacy-Preserving Text Rewriting by Learning from Human Shuo Huang William MacLean Xiaoxi Kang Anqi Wu Lizhen Qu Qiongkai Xu Zhuang Li Xingliang Yuan Gholamreza Haffari 35 0 0 06 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 28 8 0 05 Jun 2024
Delving into Differentially Private Transformer Youlong Ding Xueyang Wu Yining Meng Yonggang Luo Hao Wang Weike Pan 33 5 0 28 May 2024
$1-Diffractor: Efficient and Utility-Preserving Text Obfuscation Leveraging Word-Level Metric Differential Privacy$ 1-Diffractor: Efficient and Utility-Preserving Text Obfuscation Leveraging Word-Level Metric Differential Privacy Stephen Meisenbacher Maulik Chevli Florian Matthes 41 6 0 02 May 2024
Privacy Preserving Prompt Engineering: A Survey Kennedy Edemacu Xintao Wu 39 18 0 09 Apr 2024
A Framework for Cost-Effective and Self-Adaptive LLM Shaking and Recovery Mechanism Zhiyuan Chen Yu Li Suochao Zhang Jingbo Zhou Jiwen Zhou Chenfu Bao Dianhai Yu 26 0 0 12 Mar 2024
On Protecting the Data Privacy of Large Language Models (LLMs): A Survey Biwei Yan Kun Li Minghui Xu Yueyan Dong Yue Zhang Zhaochun Ren Xiuzhen Cheng AILaw PILM 70 76 0 08 Mar 2024
Privacy-preserving Fine-tuning of Large Language Models through Flatness Tiejin Chen Longchao Da Huixue Zhou Pingzhi Li Kaixiong Zhou Tianlong Chen Hua Wei 29 5 0 07 Mar 2024
Machine Unlearning of Pre-trained Large Language Models Jin Yao Eli Chien Minxin Du Xinyao Niu Tianhao Wang Zezhou Cheng Xiang Yue MU 50 34 0 23 Feb 2024
Privacy-Preserving Instructions for Aligning Large Language Models Da Yu Peter Kairouz Sewoong Oh Zheng Xu 34 17 0 21 Feb 2024
Neural Networks with (Low-Precision) Polynomial Approximations: New Insights and Techniques for Accuracy Improvement Chi Zhang Jingjing Fan Man Ho Au S. Yiu 22 1 0 17 Feb 2024
Towards Urban General Intelligence: A Review and Outlook of Urban Foundation Models Weijiao Zhang Jindong Han Zhao Xu Hang Ni Hao Liu Hui Xiong Hui Xiong AI4CE 77 15 0 30 Jan 2024
Private Fine-tuning of Large Language Models with Zeroth-order Optimization Xinyu Tang Ashwinee Panda Milad Nasr Saeed Mahloujifar Prateek Mittal 44 18 0 09 Jan 2024
ConfusionPrompt: Practical Private Inference for Online Large Language Models Peihua Mai Ran Yan Rui Ye Youjia Yang Yinchuan Li Yan Pang 18 1 0 30 Dec 2023
How Trustworthy are Open-Source LLMs? An Assessment under Malicious Demonstrations Shows their Vulnerabilities Lingbo Mo Boshi Wang Muhao Chen Huan Sun 29 27 0 15 Nov 2023
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
Privacy in Large Language Models: Attacks, Defenses and Future Directions Haoran Li Yulin Chen Jinglong Luo Yan Kang Xiaojin Zhang Qi Hu Chunkit Chan Yangqiu Song PILM 42 41 0 16 Oct 2023
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
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
FedFed: Feature Distillation against Data Heterogeneity in Federated Learning Zhiqin Yang Yonggang Zhang Yuxiang Zheng Xinmei Tian Hao Peng Tongliang Liu Bo Han FedML 30 61 0 08 Oct 2023
Differentially Private Natural Language Models: Recent Advances and Future Directions Lijie Hu Ivan Habernal Lei Shen Di Wang AAML 20 18 0 22 Jan 2023
Composition of Differential Privacy & Privacy Amplification by Subsampling Thomas Steinke 56 49 0 02 Oct 2022
Locally Differentially Private Sparse Vector Aggregation Mingxun Zhou Tianhao Wang T-H. Hubert Chan Giulia Fanti E. Shi FedML 37 28 0 07 Dec 2021
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
Opacus: User-Friendly Differential Privacy Library in PyTorch Ashkan Yousefpour I. Shilov Alexandre Sablayrolles Davide Testuggine Karthik Prasad ... Sayan Gosh Akash Bharadwaj Jessica Zhao Graham Cormode Ilya Mironov VLM 152 349 0 25 Sep 2021
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
Systematic Evaluation of Privacy Risks of Machine Learning Models Liwei Song Prateek Mittal MIACV 196 358 0 24 Mar 2020
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity Ulfar Erlingsson Vitaly Feldman Ilya Mironov A. Raghunathan Kunal Talwar Abhradeep Thakurta 141 420 0 29 Nov 2018
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding Alex Jinpeng Wang Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 297 6,956 0 20 Apr 2018
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation Yonghui Wu M. Schuster Z. Chen Quoc V. Le Mohammad Norouzi ... Alex Rudnick Oriol Vinyals G. Corrado Macduff Hughes J. Dean AIMat 716 6,743 0 26 Sep 2016