Differential Privacy

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30 papers in the last four weeks, up 100% on the four weeks before. 0.2% of all new papers.

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DP-MIND: Differentially private memory-guided Long context Inference
Oct 9, 2026Zhihao Liu, Yitian Cheng, Shuang Liu +3Privacy-Preserving Language Models Long-Context Language Model Inference
Zhejiang University · Ant Group · Institute of Science Tokyo +1
BRACE: Differential Privacy for Dense Associative Memory with LSR Energy
Oct 8, 2026Chang Qu, Zhaoyang ShiAssociative Memory Differential Privacy
Department of Mathematics and Statistics, University of Ottawa · Center for Applied Mathematics, Fudan University
Evaluating Sequence Assembly Strategies for Differentially Private Synthetic Time-Series Forecasting
Oct 7, 2026Guoxiong Long, Huizhen Huang, Qikun Cai +2Synthetic Data Evaluation Synthetic Data Generation
School of Computer and Big Data, Minjiang University, No. 200 Xiyuangong Road, Fuzhou, 350108, Fujian, China
Efficient Provably Private Classification with a Tabular Foundation Model
Oct 7, 2026Talal Alrawajfeh, Cristiana Diaconu, Ossi Räisä +5Privacy-Preserving ML Tabular Foundation Models
Department of Computer Science, University of Helsinki, Helsinki, Finland · Department of Engineering, University of Cambridge, Cambridge, United Kingdom · CISPA Helmholtz Center for Information Security, Saarbrücken, Germany +1
Reward-Driven Learning under Prompt-Level Differential Privacy
Oct 5, 2026Jiachen Zhao, Antonia Januszewicz, Taeho JungPrivacy-Preserving Language Models Differentially Private Stochastic Gradient Descent
University of Notre Dame
Private online learning and prediction for Littlestone classes
Oct 5, 2026Amartya SanyalPrivacy-Preserving ML Differential Privacy
Department of Computer Science University of Copenhagen
Differentially Private Mixing of Public Datasets Improves Private Learning
Oct 5, 2026Yufei Chen, Tejumade Afonja, Anvith Thudi +1Privacy-Preserving ML Differential Privacy
University of Toronto and Vector Institute, Toronto, Canada · CISPA Helmholtz Center for Information Security, Saarbrucken, Germany
DP-ES: Differentially Private Evolution Strategies for Prompt Optimization
Oct 5, 2026Ziniu Liu, Aiping Li, Yue Han +5Large Language Model-Guided Optimization Evolution Strategies
National University of Defense Technology · CRRC Zhuzhou Electric Locomotive Research Institute Co., Ltd., China Academy of Railway Sciences
Asymptotically Optimal Best Arm Identification with Fixed-Budget under Differential Privacy
Oct 3, 2026Keqin Chen, Jie Bian, Yulian Wu +1Best-Arm Identification Multi-Armed Bandits
Institute of Data Science National University of Singapore · Department of Electrical and Computer Engineering National University of Singapore · Department of Mathematics National University of Singapore
Kinematics-Induced Multimodal 3D Human Pose Estimation with Subject-Level Privacy
Oct 2, 2026Kaushik Bhargav Sivangi, Fani Deligianni3D Human Pose Estimation Multimodal Sensor Fusion
Bio-AIm Lab School of Computing Science University of Glasgow
Differential Privacy of Gradient Descent on Perturbed Objectives
Oct 2, 2026Austin Watkins, Raman AroraDifferential Privacy Gradient Descent
Johns Hopkins University Baltimore, MD 21218
HXAI: Hierarchical Privacy-Preserving Explainable AI in Distributed Energy Systems
Oct 1, 2026Poushali Sengupta, Sabita Maharjan, Frank Eliassen +1Explainable Artificial Intelligence Power Systems
Department of Informatics, University of Oslo, 0316 Oslo, Norway
Certification-Based Differentially Private Learning
Sep 30, 2026Mihnea Ghitu, Matthew WickerPrivacy-Preserving ML Differential Privacy
Department of Computing Imperial College London London, United Kingdom
PrivCert: Certifying Statement Support under Differential Privacy
Sep 30, 2026Tsubasa Takahashi, Takumi HiraokaDifferential Privacy Privacy-Utility Tradeoff
Acompany Co., Ltd.
Where Privacy Belongs: Placement Diagnosis and Certified Selection for Private Counterfactual Explanations on Graphs
Sep 29, 2026Yuxiang Yao, Zijun ZhaoCounterfactual Explanations GNN Explainability
Project Management Department, Research Center, China Life Insurance Company Ltd., Beijing, China · School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China
A Sharp Transition in Data Reconstruction under Differential Privacy
Sep 29, 2026Max Cairney-Leeming, Simone Bombari, Marco MondelliAdversarial Attacks Differential Privacy
Institute of Science and Technology Austria
Understanding Private Evolution as Learning-Augmented Clustering
Sep 29, 2026Audra McMillan, Kunal Talwar, Felix ZhouSynthetic Data Generation Differential Privacy
Apple · Yale University
Vanilla Policy Optimization Is Both Optimal and Differentially Private for Stochastic Contextual Bandits
Sep 27, 2026Idan Attias, Orin Levy, Alexander Ryabchenko +2Policy Optimization Differential Privacy
University of Illinois Chicago · Toyota Technological Institute at Chicago · Tel Aviv University +3
Geometry-Adaptive Mechanisms for Private Synthetic Data
Sep 27, 2026Raoof Zare Moayedi, Amir R. Asadi, Mohammad Hossein Yassaee +1Intrinsic Dimensionality Synthetic Data Generation
Sharif University of Technology · University of Birmingham · The Alan Turing Institute
Gap-free Differentially Private PCA for Gaussian Data
Sep 25, 2026Alina Ene, Huy L. NguyenPrincipal Component Analysis Differential Privacy
Department of Computer Science, Boston University · Khoury College of Computer and Information Science, Northeastern University
Decoupled Learning and Selection in Slate Recommendation for Privacy and Stability Under Noisy Scores
Sep 24, 2026Sam Urmian, Qinyi Liu, Mohammad KhalilLearning to Rank Differential Privacy
University of Bergen Centre for the Science of Learning & Technology (SLATE) · City University of Macau School of Education
Private Decentralized Optimization with Noise Reduction and Bias Correction
Sep 23, 2026Yizhao Fan, Wenjian Luo, Jiaojiao ZhangDifferential Privacy Variance Reduction
Harbin Institute of Technology, Shenzhen · Great Bay University
An Exposition of GPT Astra's Proof of Lower Bound on DP Continual Counting
Sep 22, 2026Jalaj UpadhyayDifferential Privacy Information-Theoretic Lower Bounds
Rutgers University
Gap-Free Streaming PCA Beyond Rank-One Updates: Near-Optimal Rates and Applications to Differential Privacy
Sep 22, 2026Anming Gu, Syamantak Kumar, Kevin Tian +1Principal Component Analysis Differential Privacy
University of Texas at Austin
Empirical Auditing of Edge-Private Graph Generators
Sep 21, 2026Anum Fatima, Stratis Limnios, James Adams +4Privacy Auditing Edge Inference
Department of Statistics University of Oxford Oxford, United Kingdom · Plenitude Consulting, London, United Kingdom · National Physical Laboratory Teddington, United Kingdom +3
Improved Private Sparse Covariance Estimation with Multiscale Threshold Tests
Sep 19, 2026Zihan ZhangCovariance Estimation Differential Privacy
Department of CSE, HKUST
Locally Private Inference for Riemannian Stochastic Optimization
Sep 18, 2026Xiaotian Chang, Yangdi Jiang, Qirui HuRiemannian Optimization Confidence Region Estimation
School of Physical and Mathematical Sciences, Nanyang Technological University · School of Statistics and Data Science, Shanghai University of Finance and Economics.
Differentially Private Semantic Plans for Aggregate Insight Generation
Sep 14, 2026Behrooz RazeghiPrivacy-Preserving Language Models Privacy-Preserving ML
School of Engineering and Applied Sciences, Harvard University
Privacy-enhanced federated learning via asynchronous aggregation and local differential perturbation
Sep 14, 2026Zhen Zhong, Shini Yang, Liesheng WeiFederated Learning Aggregation Asynchronous Federated Learning
Georgetown University, Washington, D.C., USA · LinkedIn, CA, USA · Shanghai Ocean University, Shanghai, China
SpliTEE: Fast and Private LLM Inference by Coupling GPU-Assisted Trusted Execution Environments with Differential Privacy
Sep 14, 2026Shashie Dilhara Batan Arachchige, Robin Carpentier, Hassan Jameel Asghar +1Privacy-Preserving Language Models Split Inference
School of Computing, Macquarie University

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DP-MIND: Differentially private memory-guided Long context Inference

Zhihao Liu, Yitian Cheng, Shuang Liu, Rui Wen+2

Zhejiang University · Ant Group · Institute of Science Tokyo+1

Privacy-Preserving Language Models Long-Context Language Model Inference Differential Privacy Memory-Augmented Language Models

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LLM-as-a-Service has become a dominant paradigm for accessing large language models without requiring local deployment. However, the process raises severe privacy concerns when user queries may include sensitive or confidential contexts. Differential privacy (DP) provides a principled approach to protecting such inputs, but existing DP inference methods are primarily designed for short- or moderate-context settings and struggle with million-token-scale inputs due to limited context capacity and severe utility degradation under DP perturbation. In this paper, we propose DP-MIND, a memory-guided framework that scales differentially private inference to million-token contexts. DP-MIND enables private long-context inference by locally perturbing the input and processing it chunk by chunk with a compact memory that preserves task-relevant information across the sequence. To make this memory robust to DP noise, we optimize the memory construction policy directly on perturbed inputs using reinforcement learning, guided by both final answer correctness and memory consistency. We further recover perturbation-corrupted answer spans through a local denoising module without exposing the original context to the external model. We provide theoretical privacy analysis of DP-MIND and further conduct extensive empirical analysis across multiple long-context benchmarks with context lengths up to the million-token scale, demonstrating that DP-MIND consistently outperforms existing DP and long-context inference baselines in both scalability and utility.