Tabular Diffusion Models

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Overview

Tabular diffusion models learn to generate realistic rows or fill missing values in tables containing numerical, categorical, and sometimes ordinal features, supporting data augmentation, simulation, and analysis when real data are scarce. Common approaches apply denoising to continuous and discrete features with specialized encodings, using MLPs or Transformers; newer work also explores tree-based models, conditioning, and in-context generation across datasets. These models are used for synthetic-data generation, imputation, rare-event augmentation, and probabilistic prediction, with evaluation spanning statistical fidelity, downstream task utility, diversity, and privacy. A key tension is that matching distributions does not guarantee useful, private, or semantically and causally consistent data, while results can depend strongly on benchmarks and evaluation metrics.

Latest papers

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25 papers6 papers in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

  1. DiffLTM: Continuous Diffusions Large Tabular Models for Conditional Generation

    Oct 21, 2026Alankrita Bhatt, Mukur Gupta, Andrea Montanari +1Tabular Diffusion ModelsSynthetic Tabular Data Generation

    Granica Computing Inc. · Stanford University

  2. TabGift: A Context-Efficient Foundation Model for Tabular Data Generation

    Oct 12, 2026Yu-Sheng Li, Jun-Peng Jiang, Han-Jia YeSynthetic Tabular Data GenerationGenerative Modeling

    School of Artificial Intelligence, Nanjing University, China · National Key Laboratory for Novel Software Technology, Nanjing University, China

  3. TabMosaic: Unified In-Context Diffusion for Tabular Generative Tasks

    Oct 11, 2026Jayoung Kim, Sanghyun Hong, Noseong ParkSynthetic Tabular Data GenerationTabular Diffusion Models

    KAIST · Oregon State University

  4. Beyond Distributional Fidelity: Causal-Penalized Diffusion for Synthetic Tabular Data

    Oct 8, 2026Lan Tao, Yongxian He, Shirong Xu +2Synthetic Tabular Data GenerationTabular Diffusion Models

    Department of Statistics & Data Science, University of California, Los Angeles · Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego · Wang Yanan Institute for Studies in Economics, Xiamen University

  5. Usefulness of Quantile-Aware Diffusion Modeling for Highly Imbalanced Tabular Data

    Oct 5, 2026Abu Talha, Peng Liu, Souradyuti PaulClass-Imbalanced LearningSynthetic Data Augmentation

    Indian Institute of Technology Bhilai, Durg, C.G. 491002, India · Loughborough University, Loughborough, LE11 3TU, United Kingdom

  6. CDMD: A Cross-Dataset Mixed-Type Diffusion Model for Tabular Data

    Sep 30, 2026Mohamed Amine Ketata, Maximilian Schambach, Stephan GünnemannMasked Diffusion ModelsTabular Diffusion Models

    Munich Data Science Institute, Technical University of Munich, Germany · SAP SE, Germany

  7. Beyond Distribution Matching: Semantics-Consistent Tabular Diffusion with Weak Semantic Priors

    Sep 13, 2026Yili Wang, Ruxue Shi, Mengnan Du +3Synthetic Tabular Data GenerationTabular Diffusion Models

    School of Artificial Intelligence, Jilin University, Changchun, China · School of Artificial Intelligence, The Chinese University of Hong Kong, Shenzhen, China

  8. Fast BIB simulation at a future Muon Collider with generative machine learning

    Sep 10, 2026Radha Mastandrea, Shiyu Peng, Benjamin Rosser +1Tabular Diffusion ModelsGenerative Modeling

    Enrico Fermi Institute, The University of Chicago, Chicago, IL 60637, USA · Data Science Institute, The University of Chicago, Chicago, IL 60637, USA · Department of Physics, Brown University, Providence, RI 02912, USA +1

  9. Diff-DDoS: Realistic Cyber-Physical Attack Synthesis and Robust Detection for 5G-Enabled CPS Using Tabular Diffusion Models

    Aug 18, 2026Bilal Hussain, Xiao Tang, Qinghe Du +3CybersecurityNetwork Intrusion Detection

    Division of Science, Engineering, and Health Studies, School of Professional Education and Executive Development, The Hong Kong Polytechnic University · School of Information and Communications Engineering, Xi’an Jiaotong University · Department of Computer Science, The Hang Seng University of Hong Kong +2

  10. Generating Benchmark Health Data Using a Tabular Diffusion Transformer

    Aug 14, 2026Hao Yan, Lisa Pilgram, Dan Liu +3Synthetic Tabular Data GenerationTabular Diffusion Models

    Children’s Hospital of Eastern Ontario Research Institute, Ontario, Canada · School of Epidemiology and Public Health, University of Ottawa, Ontario, Canada · Department of Nephrology and Medical Intensive Care, Charité - Universitaetsmedizin Berlin, Berlin, Germany +2

  11. Conditioning Tree-Based Diffusions and Flows for Probabilistic Tabular Regression

    Jul 30, 2026Silas KoemenFlow MatchingGradient-Boosted Decision Trees

    Independent Researcher

  12. TabSODA: Tabular Diffusion based Imputation with Skip Pattern Detection and Ordinal Awareness

    Jun 3, 2026Yuyu Chen, Taehyo Kim, Hai Shu +1Incomplete Data ImputationLearning with Missing Data

    Department of Biostatistics NYU School of Global Public Health

  13. Learning What Not to Impute: An Uncertainty-Aware Diffusion Framework for Meaningful Missingness

    Jun 3, 2026Lixing Zhang, Yidong Ouyang, Weifu Li +3Incomplete Data ImputationLearning with Missing Data

    University of Minnesota · University of California, Los Angeles · Carnegie Mellon University

  14. AugMask: Training Diffusion Models on Incomplete Tabular Data via Stochastic Augmentation and Masking

    Jun 2, 2026Jungkyu Kim, Taeyoung Park, Kibok LeeLearning with Missing DataTabular Diffusion Models

    Department of Statistics and Data Science, Yonsei University, South Korea.

  15. Geometry-Aware Tabular Diffusion

    May 23, 2026David Turtora ZagardoTabular Diffusion ModelsTabular Data Synthesis

    Independent Researcher.

  16. FERMI: Exploiting Relations for Membership Inference Against Tabular Diffusion Models

    May 12, 2026Abtin Mahyar, Masoumeh Shafieinejad, Yuhan Liu +1Membership Inference AttacksTabular Diffusion Models

    University of Waterloo · Vector Institute

  17. Active Tabular Augmentation via Policy-Guided Diffusion Inpainting

    May 11, 2026Zheyu Zhang, Shuo Yang, Bardh Prenkaj +1Data AugmentationTabular Diffusion Models

    Technical University of Munich · Munich Center for Machine Learning (MCML)

  18. On Privacy Leakage in Tabular Diffusion Models: Influential Factors, Attacker Knowledge, and Metrics

    May 7, 2026Masoumeh Shafieinejad, D. B. Emerson, Behnoosh Zamanlooy +5Data LeakageMembership Inference Attacks

    Vector Institute · McMaster University · University of Toronto +1

  19. Inference-Time Refinement Closes the Synthetic-Real Gap in Tabular Diffusion

    May 7, 2026Eugenio Lomurno, Filippo Balzarini, Francesco Benelle +2Diffusion Model GuidanceInference-Time Optimization

    Politecnico di Milano, AIRLab, Italy

  20. Extending Tabular Denoising Diffusion Probabilistic Models for Time-Series Data Generation

    Apr 6, 2026Umang Dobhal, Christina Garcia, Sozo InoueTime Series GenerationTabular Diffusion Models

  21. A Sobering Look at Tabular Data Generation via Probabilistic Circuits

    Mar 24, 2026Davide Scassola, Dylan Ponsford, Adrián Javaloy +4Synthetic Tabular Data GenerationProbabilistic Circuits

    AILAB, University of Trieste, Trieste, Italy · Aindo SpA, AREA Science Park, Trieste, Italy · School of Informatics, University of Edinburgh, Edinburgh, UK

  22. MIDST Challenge at SaTML 2025: Membership Inference over Diffusion-models-based Synthetic Tabular data

    Mar 19, 2026Masoumeh Shafieinejad, Xi He, Mahshid Alinoori +6Synthetic Data EvaluationMembership Inference Attacks

    Vector Institute · University of Waterloo · McGill University

  23. EmDT: Embedding Diffusion Transformer for Tabular Data Generation in Fraud Detection

    Mar 13, 2026En-Ya Kuo, Sebastien MotschSynthetic Data GenerationSynthetic Tabular Data Generation

    Arizona State University – School of Mathematical and Statistical Sciences, Tempe, AZ, USA

  24. XGenBoost: Synthesizing Small and Large Tabular Datasets with XGBoost

    Mar 6, 2026Jim Achterberg, Marcel Haas, Bram van Dijk +1Synthetic Tabular Data GenerationTabular Diffusion Models

    Public Health & Primary Care, Leiden University Medical Center, Leiden, The Netherlands · Research and Development, Statistics Netherlands (CBS), The Hague, The Netherlands · Leiden Institute of Advanced Computer Science, Leiden University, Leiden, The Netherlands

  25. TabDLM: Free-Form Tabular Data Generation via Joint Numerical-Language Diffusion

    Feb 26, 2026Donghong Cai, Jiarui Feng, Yanbo Wang +3Synthetic Tabular Data GenerationTabular Diffusion Models

    Washington University in St. Louis · Peking University · Ant Group