mlsanityData to 7 Oct 2026

Synthetic Data -- what, why and how?

arXiv 2205.03257 ↗First posted 6 May 2022cs.LGcited by 66

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Abstract (arXiv)

This explainer document aims to provide an overview of the current state of the rapidly expanding work on synthetic data technologies, with a particular focus on privacy. The article is intended for a non-technical audience, though some formal definitions have been given to provide clarity to specialists. This article is intended to enable the reader to quickly become familiar with the notion of synthetic data, as well as understand some of the subtle intricacies that come with it. We do believe that synthetic data is a very useful tool, and our hope is that this report highlights that, while drawing attention to nuances that can easily be overlooked in its deployment.

Key facts. Cited by 66 papers in the map (data through 7 Oct 2026). Builds on 114 of its 220 references that are in the map. First posted on arXiv 6 May 2022.

Builds on

114 of 220 references.

References · 114

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38 more
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50 most cited of 114 All 114 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 7; 2023: 20; 2024: 17; 2025: 11; 2026: 11.

66 papers.

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  1. 2022Brain Imaging Generation with Latent Diffusion Modelscited by 267
  2. 2024Why Tabular Foundation Models Should Be a Research Prioritycited by 103
  3. 2023Synthcity: facilitating innovative use cases of synthetic data in different data modalitiescited by 76
  4. 2023SoK: Privacy-Preserving Data Synthesiscited by 37
  5. 2023Learning from data with structured missingnesscited by 24
  6. 2024From Pixel to Cancer: Cellular Automata in Computed Tomographycited by 20
  7. 2023SurvivalGAN: Generating Time-to-Event Data for Survival Analysiscited by 17
  8. 2024Systematic Assessment of Tabular Data Synthesiscited by 17
  9. 2023Mask-conditioned latent diffusion for generating gastrointestinal polyp imagescited by 16
  10. 2022Morphology-preserving Autoregressive 3D Generative Modelling of the Braincited by 15
  11. 2023Advances in Embodied Navigation Using Large Language Models: A Surveycited by 14
  12. 2024From Efficient Multimodal Models to World Models: A Surveycited by 13
38 more
  1. 2024Privacy Vulnerabilities in Marginals-based Synthetic Datacited by 10
  2. 2022Non-Imaging Medical Data Synthesis for Trustworthy AI: A Comprehensive Surveycited by 9
  3. 2023Post-processing Private Synthetic Data for Improving Utility on Selected Measurescited by 9
  4. 2022Human-in-the-Loop Mixupcited by 8
  5. 2022On the Utility Recovery Incapability of Neural Net-based Differential Private Tabular Training Data Synthesizer under Privacy Deregulationcited by 8
  6. 2023Utility Theory of Synthetic Data Generationcited by 8
  7. 2023Assessment of Differentially Private Synthetic Data for Utility and Fairness in End-to-End Machine Learning Pipelines for Tabular Datacited by 8
  8. 2022What Does DALL-E 2 Know About Radiology?cited by 7
  9. 2023Boosting Data Analytics With Synthetic Volume Expansioncited by 7
  10. 2024Latent Diffusion Models for Attribute-Preserving Image Anonymizationcited by 7
  11. 2023Astroformer: More Data Might not be all you need for Classificationcited by 6
  12. 2024Faraday: Synthetic Smart Meter Generator for the smart gridcited by 6
  13. 2024Synthetic Data: Revisiting the Privacy-Utility Trade-offcited by 6
  14. 2024IDNet: A Novel Dataset for Identity Document Analysis and Fraud Detectioncited by 6
  15. 2024Tabular Data Synthesis with Differential Privacy: A Surveycited by 6
  16. 2025Thinking Beyond Tokens: From Brain-Inspired Intelligence to Cognitive Foundations for Artificial General Intelligence and its Societal Impactcited by 6
  17. 2023RetailSynth: Synthetic Data Generation for Retail AI Systems Evaluationcited by 5
  18. 2024Advancing Retail Data Science: Comprehensive Evaluation of Synthetic Datacited by 5
  19. 2022Provable Membership Inference Privacycited by 4
  20. 2023A Unified View of Differentially Private Deep Generative Modelingcited by 4
  21. 2023A Unified Framework for Generative Data Augmentation: A Comprehensive Surveycited by 4
  22. 2023Privacy Measurement in Tabular Synthetic Data: State of the Art and Future Research Directionscited by 4
  23. 2024Does Differentially Private Synthetic Data Lead to Synthetic Discoveries?cited by 4
  24. 2025Concept-as-Tree: A Controllable Synthetic Data Framework Makes Stronger Personalized VLMscited by 4
  25. 2025FairCauseSyn: Towards Causally Fair LLM-Augmented Synthetic Data Generationcited by 3
  26. 2023Fairness in AI and Its Long-Term Implications on Societycited by 2
  27. 2024Differentially Private Synthetic Data with Private Density Estimationcited by 2
  28. 2024Convex space learning for tabular synthetic data generationcited by 2
  29. 2024Defining 'Good': Evaluation Framework for Synthetic Smart Meter Datacited by 2
  30. 2025Filtering with Confidence: When Data Augmentation Meets Conformal Predictioncited by 2
  31. 2023Differentially Private Synthetic Data Using KD-Treescited by 1
  32. 2023A supervised generative optimization approach for tabular datacited by 1
  33. 2023Private Synthetic Data Meets Ensemble Learningcited by 1
  34. 2025Zero-shot generation of synthetic neurosurgical data with large language modelscited by 1
  35. 2025Exploring the Effectiveness of Deep Features from Domain-Specific Foundation Models in Retinal Image Synthesiscited by 1
  36. 2025PRO: Projection Domain Synthesis for CT Imagingcited by 1
  37. 2025Democratizing Tabular Data Access with an Openunicodex2013Source Syntheticunicodex2013Data SDKcited by 1
  38. 2026CasualSynth: Generating Structurally Sound Synthetic Datacited by 1

50 most cited of 66 All 66 (JSON)