mlsanityData to 7 Oct 2026

Privacy-preserving tabular data synthesis

53 papers0 this weekMedium confidence in this grouping: mostly one topic, with blurry edgesMedium confidence in this grouping: mostly one topic, with blurry edges · About

Keywords: privacy, tabular, synthetic, private, llms

Key facts. Privacy-preserving tabular data synthesis: 53 papers on arXiv since 2021 (data through 7 Oct 2026). 12 of its 53 mapped papers (23%) cite “Mixed-Type Tabular Data Synthesis with Score-based Diffusion in Latent Space” (2023, arXiv 2310.09656). 9 of its 53 mapped papers (17%) cite “Differentially Private Synthetic Data via Foundation Model APIs 2: Text” (2024, arXiv 2403.01749). 2 new papers 17 Sep–7 Oct.

What’s new

17 Sep – 7 Oct 2026

2 new since 17 Sep

  1. Synthesis Without Training: An Inference-Only Pipeline for Tabular, Temporal, and Relational Synthetic Data also fits: LLM synthetic data generation
  2. TabFM-Auto: Self-Evolving Pipelines for Tabular Foundation Models

Foundations

Most cited by papers here

  1. Mixed-Type Tabular Data Synthesis with Score-based Diffusion in Latent Space2023cited by 12 here
  2. Differentially Private Synthetic Data via Foundation Model APIs 2: Text2024cited by 9 here
  3. Contrastive Private Data Synthesis via Weighted Multi-PLM Fusion2025cited by 4 here
  4. TabuLa: Harnessing Language Models for Tabular Data Synthesis2023cited by 3 here
  5. Differentially Private Synthetic Data via APIs 3: Using Simulators Instead of Foundation Model2025cited by 3 here

Lineage

The papers this direction builds on, oldest first.

Each paper on the line cites the one before.

  1. 2024Differentially Private Synthetic Data via Foundation Model APIs 2: Textcited by 9 here
  2. 2025Contrastive Private Data Synthesis via Weighted Multi-PLM Fusioncited by 4 here
  3. 2025Differentially Private Synthetic Data via APIs 3: Using Simulators Instead of Foundation Modelcited by 3 here
  4. 2025POPri: Private Federated Learning using Preference-Optimized Synthetic Datacited by 3 here
20 more it builds on, not in this chain
  1. 2022Self-Instruct: Aligning Language Models with Self-Generated Instructionscited by 2 here
  2. 2023Does Synthetic Data Generation of LLMs Help Clinical Text Mining?cited by 2 here
  3. 2023Generating Faithful Synthetic Data with Large Language Models: A Case Study in Computational Social Sciencecited by 1 here
  4. 2023Synthetic Data Generation with Large Language Models for Text Classification: Potential and Limitationscited by 3 here
  5. 2023Mixed-Type Tabular Data Synthesis with Score-based Diffusion in Latent Spacecited by 12 here
  6. 2023TabuLa: Harnessing Language Models for Tabular Data Synthesiscited by 3 here
  7. 2024Systematic Assessment of Tabular Data Synthesiscited by 1 here
  8. 2024DataDreamer: A Tool for Synthetic Data Generation and Reproducible LLM Workflowscited by 1 here
  9. 2024Generative AI for Synthetic Data Generation: Methods, Challenges and the Futurecited by 1 here
  10. 2024Best Practices and Lessons Learned on Synthetic Datacited by 1 here
  11. 2024EPIC: Effective Prompting for Imbalanced-Class Data Synthesis in Tabular Data Classification via Large Language Modelscited by 2 here
  12. 2024A Multi-Faceted Evaluation Framework for Assessing Synthetic Data Generated by Large Language Modelscited by 1 here
  13. 2024ClavaDDPM: Multi-relational Data Synthesis with Cluster-guided Diffusion Modelscited by 2 here
  14. 2024Differentially Private Tabular Data Synthesis using Large Language Modelscited by 1 here
  15. 2024A Synthetic Dataset for Personal Attribute Inferencecited by 1 here
  16. 2024On LLMs-Driven Synthetic Data Generation, Curation, and Evaluation: A Surveycited by 3 here
  17. 2024Scaling Synthetic Data Creation with 1,000,000,000 Personascited by 1 here
  18. 2024HARMONIC: Harnessing LLMs for Tabular Data Synthesis and Privacy Protectioncited by 1 here
  19. 2024Generated Data with Fake Privacy: Hidden Dangers of Fine-tuning Large Language Models on Generated Datacited by 1 here
  20. 2024Knowledge Distillation Using Frontier Open-source LLMs: Generalizability and the Role of Synthetic Datacited by 1 here

The 24 most cited of 27.

Browse

30 of 53, ranked 6–35

  1. 6POPri: Private Federated Learning using Preference-Optimized Synthetic Data20253
  2. 7EPIC: Effective Prompting for Imbalanced-Class Data Synthesis in Tabular Data Classification via Large Language Models20242
  3. 8ClavaDDPM: Multi-relational Data Synthesis with Cluster-guided Diffusion Models20242
  4. 9The Canary's Echo: Auditing Privacy Risks of LLM-Generated Synthetic Text20251
  5. 10RewardDS: Privacy-Preserving Fine-Tuning for Large Language Models via Reward Driven Data Synthesis20251
  6. 11Systematic Assessment of Tabular Data Synthesis20241
  7. 12A Multi-Faceted Evaluation Framework for Assessing Synthetic Data Generated by Large Language Models20241
  8. 13Differentially Private Tabular Data Synthesis using Large Language Models20241
  9. 14A Synthetic Dataset for Personal Attribute Inference20241
  10. 15HARMONIC: Harnessing LLMs for Tabular Data Synthesis and Privacy Protection20241
All 30
  1. 16Generated Data with Fake Privacy: Hidden Dangers of Fine-tuning Large Language Models on Generated Data20241
  2. 17Continual Pretraining on Encrypted Synthetic Data for Privacy-Preserving LLMs20260
  3. 18EPSVec: Efficient and Private Synthetic Data Generation via Dataset Vectors20260
  4. 19PluRel: Synthetic Data unlocks Scaling Laws for Relational Foundation Models20260
  5. 20Improving TabPFN's Synthetic Data Generation by Integrating Causal Structure20260
  6. 21ReTabSyn: Realistic Tabular Data Synthesis via Reinforcement Learning20260
  7. 22Private Seeds, Public LLMs: Realistic and Privacy-Preserving Synthetic Data Generation20260
  8. 23Self-Improving Tabular Language Models via Iterative Reward-Guided Post-Training20260
  9. 24Generative Synthetic Data for Causal Inference: Pitfalls, Remedies, and Opportunities20260
  10. 25Concordia: Self-Improving Synthetic Tables for Federated LLMs20260
  11. 26Differentially Private Synthetic Data via APIs 4: Tabular Data20260
  12. 27TabClaw: An Interactive and Self-Evolving Agent for Spreadsheet Manipulation and Table Reasoning20260
  13. 28Phantoms and Disclosures: A Statistical Framework for Auditing Privacy in Synthetic Data20260
  14. 29Beyond the Stitching Assumption: A Unified Framework for Multimodal Synthetic Data Evaluation via Semantic Quantization20260
  15. 30Creation begins with understanding: LLMs as strategy designers for privacy-preserving tabular data synthesis20260
  16. 31SampleLLM: Optimizing Tabular Data Synthesis in Recommendations20250
  17. 32Tabby: A Language Model Architecture for Tabular and Structured Data Synthesis20250
  18. 33TabularQGAN: A quantum generative model for tabular data synthesis20250
  19. 34FairCauseSyn: Towards Causally Fair LLM-Augmented Synthetic Data Generation20250
  20. 35Towards High Supervised Learning Utility Training Data Generation: Data Pruning and Column Reordering20250