Differentially Private Synthetic Data Generation

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21 papers4 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

  1. SHIP: Structured and Hierarchical Insight with Privacy

    Oct 15, 2026Kai Chen, Guisi Ni, Albert Cheu +4Differentially Private Synthetic Data GenerationPrivacy-Utility Tradeoff

    University of Virginia · Google Research

  2. Tight End-to-End Accounting for Differentially Private Synthetic Data

    Oct 12, 2026Georgi Ganev, Vadym Doroshenko, Arun Ganesh +3Differential PrivacyDifferentially Private Synthetic Data Generation

    UCL · SAS · Google +3

  3. Understanding Private Evolution as Learning-Augmented Clustering

    Sep 29, 2026Audra McMillan, Kunal Talwar, Felix ZhouDifferentially Private Synthetic Data GenerationSynthetic Data Generation

    Apple · Yale University

  4. Geometry-Adaptive Mechanisms for Private Synthetic Data

    Sep 27, 2026Raoof Zare Moayedi, Amir R. Asadi, Mohammad Hossein Yassaee +1Intrinsic DimensionalityDifferentially Private Synthetic Data Generation

    Sharif University of Technology · University of Birmingham · The Alan Turing Institute

  5. Subgroup Membership Inference Audits of Differentially Private Synthetic Text

    Sep 9, 2026Yidan Sun, Viktor Schlegel, Srinivasan Nandakumar +2Privacy AuditingMembership Inference Attacks

    Imperial College London, Imperial Global Singapore · Nanyang Technological University, Singapore · Imperial College London, United Kingdom

  6. Where to Intervene? Benchmarking Fairness-Aware Learning on Differentially Private Synthetic Tabular Data

    Jul 8, 2026Vinícius Gabriel Angelozzi, Héber H. ArcoleziAlgorithmic FairnessGroup Fairness

    Centre Inria de l’Université Grenoble Alpes · ÉTS Montréal, Inria Grenoble

  7. Fixed-Parameter Tractability of Private Synthetic Data Generation

    Jun 9, 2026Badih Ghazi, Cristóbal Guzmán, Pritish Kamath +3Differentially Private Synthetic Data GenerationSynthetic Data Generation

    Google Deepmind · Institute for Mathematical and Computational Engineering, Faculty of Mathematics and School of Engineering, Pontificia Universidad Cat´olica de Chile · Google Research

  8. Differentially Private Synthetic Data via APIs 4: Tabular Data

    Jun 6, 2026Toan Tran, Arturs Backurs, Zinan Lin +3Synthetic Data GenerationSynthetic Tabular Data Generation

    Emory University · Microsoft Research

  9. ContinuousBench: Can Differentially Private Synthetic Text Improve Capabilities?

    Jun 1, 2026Peihan Liu, Lucas Rosenblatt, Weiwei Kong +7Privacy-Preserving Language ModelsSynthetic Benchmark Generation

    Columbia University · Work done as a Student Researcher at Google · NYU +4

  10. Differentially Private Preference Data Synthesis for Large Language Model Alignment

    May 29, 2026Fengyu Gao, Jing YangPairwise Preference LearningLLM Alignment

    Department of Computer Science, University of Virginia, Charlottesville, Virginia, USA · Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, Virginia, USA.

  11. PATE-TabTransGAN: Differentially Private Synthetic Tabular Data Generation via Transformer-Based Student Discrimination

    May 26, 2026M. Youssef, M. WoźniakSynthetic Tabular Data GenerationDifferential Privacy

    Wrocław University of Science and Technology, Wrocław, Poland

  12. Tight Auditing of Differential Privacy in MST and AIM

    Apr 20, 2026Georgi Ganev, Meenatchi Sundaram Muthu Selva Annamalai, Bogdan KulynychPrivacy AuditingSynthetic Data Generation

    1UCL · 2SAS · 3Lausanne University Hospital

  13. Evaluating LLM Simulators as Differentially Private Data Generators

    Apr 16, 2026Nassima M. Bouzid, Dehao Yuan, Nam H. Nguyen +1Synthetic Data GenerationDifferential Privacy

    Capital One

  14. Private Seeds, Public LLMs: Realistic and Privacy-Preserving Synthetic Data Generation

    Apr 8, 2026Qian Ma, Sarah RajtmajerPrivacy-Preserving Language ModelsSynthetic Data Generation

    Information Sciences and Technology, The Pennsylvania State University

  15. Stable and Privacy-Preserving Synthetic Educational Data with Empirical Marginals: A Copula-Based Approach

    Apr 5, 2026Gabriel Diaz Ramos, Lorenzo Luzi, Debshila Basu Mallick +1Differentially Private Synthetic Data GenerationSynthetic Data Generation

    Rice University · OpenStax · Rice University, OpenStax

  16. REAEDP: Entropy-Calibrated Differentially Private Data Release with Formal Guarantees and Attack-Based Evaluation

    Mar 14, 2026Bo Ma, Jinsong Wu, Wei Qi YanDifferentially Private Synthetic Data GenerationDifferential Privacy

    School of Mathematics and Computer Engineering, Auckland University of Technology, Auckland 1024 New Zealand · Resideo Technologies, Inc., Austin, TX 78759, USA · Department of Artificial Intelligence, Guilin University of Electronic Technology, Gui Lin, China +1

  17. MAPLE: Metadata Augmented Private Language Evolution

    Feb 26, 2026Eli Chien, Yuzheng Hu, Ryan McKenna +3Privacy-Preserving Language ModelsDifferentially Private Synthetic Data Generation

    National Taiwan University · University of Illinois Urbana-Champaign · Google Research +1

  18. DP-RFT: Learning to Generate Synthetic Text via Differentially Private Reinforcement Fine-Tuning

    Feb 20, 2026Fangyuan Xu, Sihao Chen, Zinan Lin +13Differentially Private Synthetic Data GenerationSynthetic Data Generation for Language Models

    New York University · Microsoft · University of Southern California

  19. Beyond One-Size-Fits-All: Neural Networks for Differentially Private Tabular Data Synthesis

    Nov 17, 2025Kai Chen, Chen Gong, Tianhao WangSynthetic Data GenerationSynthetic Tabular Data Generation

    University of Virginia Charlottesville, USA

  20. Privacy-Preserving Generation of Clinical Narratives from Medical Terminologies

    Sep 13, 2025Yuping Wu, Viktor Schlegel, Warren Del-Pinto +11Medical Report GenerationHealthcare

    Univeristy of Manchester · Imperial College London, Imperial Global Singapore · Khoo Teck Puat Hospital, Singapore +2

  21. Differentially Private Synthetic Data via APIs 3: Using Simulators Instead of Foundation Model

    Feb 8, 2025Zinan Lin, Tadas Baltrusaitis, Wenyu Wang +1Differentially Private Synthetic Data GenerationSynthetic Data Generation

    Microsoft Research Redmond, WA, USA · Microsoft Cambridge, UK · Redmond, WA, USA