Title
Understanding Users' Security and Privacy Concerns and Attitudes Towards Conversational AI Platforms Mutahar Ali Arjun Arunasalam Habiba Farrukh SILM 72 0 0 09 Apr 2025
Empirical Privacy Variance Yuzheng Hu Fan Wu Ruicheng Xian Yuhang Liu Lydia Zakynthinou Pritish Kamath Chiyuan Zhang David A. Forsyth 75 0 0 16 Mar 2025
Differentially Private Synthetic Data via APIs 3: Using Simulators Instead of Foundation Model Zinan Lin Tadas Baltrusaitis Wenyu Wang Sergey Yekhanin SyDa 114 1 0 08 Feb 2025
FedTLU: Federated Learning with Targeted Layer Updates Jong-Ik Park Carlee Joe-Wong FedML 122 0 0 28 Jan 2025
Privacy in Fine-tuning Large Language Models: Attacks, Defenses, and Future Directions Hao Du Shang Liu Lele Zheng Yang Cao Atsuyoshi Nakamura Lei Chen AAML 130 3 0 21 Dec 2024
DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators Tejumade Afonja Hui-Po Wang Raouf Kerkouche Mario Fritz SyDa 138 2 0 03 Dec 2024
DiSK: Differentially Private Optimizer with Simplified Kalman Filter for Noise Reduction Xinwei Zhang Zhiqi Bu Borja Balle Mingyi Hong Meisam Razaviyayn Vahab Mirrokni 94 2 0 04 Oct 2024
Differentially Private Kernel Density Estimation Erzhi Liu Jerry Yao-Chieh Hu Alex Reneau Zhao Song Han Liu 80 3 0 03 Sep 2024
ObfuscaTune: Obfuscated Offsite Fine-tuning and Inference of Proprietary LLMs on Private Datasets Ahmed Frikha Nassim Walha Ricardo Mendes Krishna Kanth Nakka Xue Jiang Xuebing Zhou 87 3 0 03 Jul 2024
Noise-Aware Differentially Private Regression via Meta-Learning Ossi Raisa Stratis Markou Matthew Ashman W. Bruinsma Marlon Tobaben Antti Honkela Richard Turner 98 1 0 12 Jun 2024
PrivacyRestore: Privacy-Preserving Inference in Large Language Models via Privacy Removal and Restoration Huiping Zhuang Jianwei Wang Zhengdong Lu Huiping Zhuang Haoran Li Huiping Zhuang Cen Chen RALM KELM 62 8 0 03 Jun 2024
DP-DyLoRA: Fine-Tuning Transformer-Based Models On-Device under Differentially Private Federated Learning using Dynamic Low-Rank Adaptation Jie Xu Karthikeyan P. Saravanan Rogier van Dalen Haaris Mehmood David Tuckey Mete Ozay 97 6 0 10 May 2024
Private Fine-tuning of Large Language Models with Zeroth-order Optimization Xinyu Tang Ashwinee Panda Milad Nasr Saeed Mahloujifar Prateek Mittal 97 19 0 09 Jan 2024
Hot PATE: Private Aggregation of Distributions for Diverse Task Edith Cohen Benjamin Cohen-Wang Xin Lyu Jelani Nelson Tamas Sarlos Uri Stemmer 72 3 0 04 Dec 2023
Critical Influence of Overparameterization on Sharpness-aware Minimization Sungbin Shin Dongyeop Lee Maksym Andriushchenko Namhoon Lee AAML 69 1 0 29 Nov 2023
Privately Aligning Language Models with Reinforcement Learning Fan Wu Huseyin A. Inan A. Backurs Varun Chandrasekaran Janardhan Kulkarni Robert Sim 61 7 0 25 Oct 2023
DP-Forward: Fine-tuning and Inference on Language Models with Differential Privacy in Forward Pass Minxin Du Xiang Yue Sherman S. M. Chow Tianhao Wang Chenyu Huang Huan Sun SILM 66 61 0 13 Sep 2023
Unlocking Accuracy and Fairness in Differentially Private Image Classification Leonard Berrada Soham De J. Shen Jamie Hayes Robert Stanforth David Stutz Pushmeet Kohli Samuel L. Smith Borja Balle 41 15 0 21 Aug 2023
Large-Scale Public Data Improves Differentially Private Image Generation Quality Ruihan Wu Chuan Guo Kamalika Chaudhuri 65 2 0 04 Aug 2023
Harnessing large-language models to generate private synthetic text Alexey Kurakin Natalia Ponomareva Umar Syed Liam MacDermed Andreas Terzis SILM SyDa 48 38 0 02 Jun 2023
Differentially Private Synthetic Data via Foundation Model APIs 1: Images Zinan Lin Sivakanth Gopi Janardhan Kulkarni Harsha Nori Sergey Yekhanin 79 38 0 24 May 2023
Privacy-Preserving Prompt Tuning for Large Language Model Services Yansong Li Zhixing Tan Yang Liu SILM VLM 67 65 0 10 May 2023
Advancing Differential Privacy: Where We Are Now and Future Directions for Real-World Deployment Rachel Cummings Damien Desfontaines David Evans Roxana Geambasu Yangsibo Huang ... Li Xiong Sergey Yekhanin Da Yu Huanyu Zhang Wanrong Zhang 26 44 0 14 Apr 2023
Differentially Private Diffusion Models Generate Useful Synthetic Images Sahra Ghalebikesabi Leonard Berrada Sven Gowal Ira Ktena Robert Stanforth Jamie Hayes Soham De Samuel L. Smith Olivia Wiles Borja Balle DiffM 50 69 0 27 Feb 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 37 37 0 19 Feb 2023
Position: Considerations for Differentially Private Learning with Large-Scale Public Pretraining Florian Tramèr Gautam Kamath Nicholas Carlini SILM 58 71 0 13 Dec 2022
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 77 47 0 03 Dec 2022
Synthetic Text Generation with Differential Privacy: A Simple and Practical Recipe Xiang Yue Huseyin A. Inan Xuechen Li Girish Kumar Julia McAnallen Hoda Shajari Huan Sun David Levitan Robert Sim 69 80 0 25 Oct 2022
Differentially Private Optimization on Large Model at Small Cost Zhiqi Bu Yu Wang Sheng Zha George Karypis 65 52 0 30 Sep 2022
Pre-trained Perceptual Features Improve Differentially Private Image Generation Fredrik Harder Milad Jalali Asadabadi Danica J. Sutherland Mijung Park 56 28 0 25 May 2022
Unlocking High-Accuracy Differentially Private Image Classification through Scale Soham De Leonard Berrada Jamie Hayes Samuel L. Smith Borja Balle 53 223 0 28 Apr 2022
Mixed Differential Privacy in Computer Vision Aditya Golatkar Alessandro Achille Yu Wang Aaron Roth Michael Kearns Stefano Soatto PICV VLM 53 49 0 22 Mar 2022
Submix: Practical Private Prediction for Large-Scale Language Models Antonio A. Ginart Laurens van der Maaten James Zou Chuan Guo 44 22 0 04 Jan 2022
Public Data-Assisted Mirror Descent for Private Model Training Ehsan Amid Arun Ganesh Rajiv Mathews Swaroop Indra Ramaswamy Shuang Song Thomas Steinke Vinith Suriyakumar Om Thakkar Abhradeep Thakurta 38 50 0 01 Dec 2021
Large-Scale Differentially Private BERT Rohan Anil Badih Ghazi Vineet Gupta Ravi Kumar Pasin Manurangsi 48 133 0 03 Aug 2021
Benchmarking Differential Privacy and Federated Learning for BERT Models Priya Basu Tiasa Singha Roy Rakshit Naidu Zumrut Muftuoglu Sahib Singh Fatemehsadat Mireshghallah FedML AI4MH 59 50 0 26 Jun 2021
BitFit: Simple Parameter-efficient Fine-tuning for Transformer-based Masked Language-models Elad Ben-Zaken Shauli Ravfogel Yoav Goldberg 130 1,191 0 18 Jun 2021
LoRA: Low-Rank Adaptation of Large Language Models J. E. Hu Yelong Shen Phillip Wallis Zeyuan Allen-Zhu Yuanzhi Li Shean Wang Lu Wang Weizhu Chen OffRL AI4TS AI4CE ALM AIMat 191 9,946 0 17 Jun 2021
Large Scale Private Learning via Low-rank Reparametrization Da Yu Huishuai Zhang Wei Chen Jian Yin Tie-Yan Liu 42 102 0 17 Jun 2021
Compacter: Efficient Low-Rank Hypercomplex Adapter Layers Rabeeh Karimi Mahabadi James Henderson Sebastian Ruder MoE 79 479 0 08 Jun 2021
Numerical Composition of Differential Privacy Sivakanth Gopi Y. Lee Lukas Wutschitz 32 176 0 05 Jun 2021
The Power of Scale for Parameter-Efficient Prompt Tuning Brian Lester Rami Al-Rfou Noah Constant VPVLM 440 3,952 0 18 Apr 2021
Do Not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning Da Yu Huishuai Zhang Wei Chen Tie-Yan Liu FedML SILM 99 113 0 25 Feb 2021
Leveraging Public Data for Practical Private Query Release Terrance Liu G. Vietri Thomas Steinke Jonathan R. Ullman Zhiwei Steven Wu 168 58 0 17 Feb 2021
Prefix-Tuning: Optimizing Continuous Prompts for Generation Xiang Lisa Li Percy Liang 159 4,167 0 01 Jan 2021
Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning Armen Aghajanyan Luke Zettlemoyer Sonal Gupta 75 549 1 22 Dec 2020
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 398 1,868 0 14 Dec 2020
When is Memorization of Irrelevant Training Data Necessary for High-Accuracy Learning? Gavin Brown Mark Bun Vitaly Feldman Adam D. Smith Kunal Talwar 272 93 0 11 Dec 2020
AdapterDrop: On the Efficiency of Adapters in Transformers Andreas Rucklé Gregor Geigle Max Glockner Tilman Beck Jonas Pfeiffer Nils Reimers Iryna Gurevych 83 259 0 22 Oct 2020
Enabling Fast Differentially Private SGD via Just-in-Time Compilation and Vectorization P. Subramani Nicholas Vadivelu Gautam Kamath 31 83 0 18 Oct 2020