Controllable Tabular Data Synthesis Using Diffusion Models
Summary: Unconditional tabular diffusion is learned, with lightweight controllers enforcing user-defined conditions (fixed attributes, cross-table correlations). A correlation-aware sampler preserves realism under control, delivering SOTA results. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Tongyu Liu (Renmin University of China)
- 2. Ju Fan (Renmin University of China)
- 3. Nan Tang (Hong Kong University of Science and Technology)
- 4. Guoliang Li (Tsinghua University)
- 5. Xiaoyong Du (Renmin University of China)
BibTeX Citation
@inproceedings{liu_sigmod24,
title = {{Controllable Tabular Data Synthesis Using Diffusion Models}},
author = {Liu, Tongyu and Fan, Ju and Tang, Nan and Li, Guoliang and Du, Xiaoyong},
series = {{SIGMOD} '24},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3639283},
url = {https://dl.acm.org/doi/10.1145/3639283},
year = {2024}
}
Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,272 | NeurBench: A Benchmark Suite for Learned Database Components with Drift Modeling: [Experiments & Analysis] | 2026 | SIGMOD | 5.093636e-05 |
| 10,276 | OctoSelector: Efficient and Effective Batch-Aware Model Selection for Large Language Models | 2026 | SIGMOD | 5.093636e-05 |
| 10,282 | Prism: Private Relational Data Synthesis with Language Models | 2026 | SIGMOD | 5.093636e-05 |
| 10,416 | WaveStitch: Flexible and Fast Conditional Time Series Generation With Diffusion Models | 2026 | SIGMOD | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 9 of 9 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 401 | Deep Unsupervised Cardinality Estimation | 2020 | VLDB | 0.00019092557 |
| 1,169 | PrivBayes: Private Data Release via Bayesian Networks | 2014 | SIGMOD | 0.00011838753 |
| 1,573 | Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries | 2020 | SIGMOD | 0.00010328171 |
| 2,019 | RPT: Relational Pre-trained Transformer Is Almost All You Need towards Democratizing Data Preparation | 2021 | VLDB | 9.2983994e-05 |
| 2,129 | Data Synthesis based on Generative Adversarial Networks | 2018 | VLDB | 9.1266572e-05 |
| 4,261 | Relational Data Synthesis using Generative Adversarial Networks: A Design Space Exploration | 2020 | VLDB | 6.7982037e-05 |
| 4,835 | Adaptive Data Augmentation for Supervised Learning over Missing Data | 2021 | VLDB | 6.486592e-05 |
| 5,105 | SAM: Database Generation from Query Workloads with Supervised Autoregressive Models | 2022 | SIGMOD | 6.3628539e-05 |
| 7,556 | ReStore - Neural Data Completion for Relational Databases | 2021 | SIGMOD | 5.5997742e-05 |
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