Synthetic Data Generation papers, 2023–2026

Key findings

• Synthetic Data Generation went from 72 papers in 2023 to 96 in 2026, roughly 1.3x in three years.
• NeurIPS publishes the most Synthetic Data Generation work: 114 papers from 2023 to 2026, 41% of the four-venue total.
• The fastest-growing overlap is with Diffusion Models: papers tagged with both rose from 6 in 2023 to 20 in 2026.
• Among the 5 topics under Data-Centric AI, it ranks #1 by 2026 paper count; the fastest grower in the group, Weak Supervision, is up 1.3x versus 1.3x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026Breaking the Quality–Privacy Tradeoff in Tabular Data Generation via In-Context Learning
• ICML 2026Active Tabular Augmentation via Policy-Guided Diffusion Inpainting
• ICLR 2026Critic–Adviser–Reviser Cyclic Refinement: Towards High-Quality EMR Corpus Generation with LLMs
• CVPR 2026Beyond Objects Contextual Synthetic Data Generation for Fine-Grained Classification
• NeurIPS 2025Achilles' Heel of Mamba: Essential difficulties of the Mamba architecture demonstrated by synthetic data
• ICML 2025Synthetic Text Generation for Training Large Language Models via Gradient Matching
• ICLR 2025Scaling Instruction-tuned LLMs to Million-token Contexts via Hierarchical Synthetic Data Generation
• CVPR 2025Synthetic Visual Genome
• NeurIPS 2024DECO-Bench: Unified Benchmark for Decoupled Task-Agnostic Synthetic Data Release
• ICML 2024CaRiNG: Learning Temporal Causal Representation under Non-Invertible Generation Process
• ICLR 2024A Linear Algebraic Framework for Counterfactual Generation
• CVPR 2024Learning from Synthetic Human Group Activities
• NeurIPS 2023[Re] $\mathcal{G}$-Mixup: Graph Data Augmentation for Graph Classification
• ICML 2023Data Feedback Loops: Model-driven Amplification of Dataset Biases
• ICLR 2023Synthetic Data Generation of Many-to-Many Datasets via Random Graph Generation
• CVPR 2023Fake It Till You Make It: Learning Transferable Representations From Synthetic ImageNet Clones
• NeurIPS 2026Learning with Synthetic Data via SGD in High-Dimensional Linear Regression
• ICML 2026Counterfactual Residual Data Augmentation for Regression
• ICLR 2026Making, Not Taking, the Best of N
• CVPR 2026Order Matters 3D Shape Generation from Sequential VR Sketches

All Synthetic Data Generation papers

45 papers, page 1 of 1

1. NeurIPS 2023[Re] $\mathcal{G}$-Mixup: Graph Data Augmentation for Graph Classification
2. NeurIPS 20234D Panoptic Scene Graph Generation
3. NeurIPS 2023Adaptive Principal Component Regression with Applications to Panel Data
4. NeurIPS 2023Back-Modality: Leveraging Modal Transformation for Data Augmentation
5. NeurIPS 2023Benchmarking Distribution Shift in Tabular Data with TableShift
6. NeurIPS 2023Can You Rely on Your Model Evaluation? Improving Model Evaluation with Synthetic Test Data
7. NeurIPS 2023CityRefer: Geography-aware 3D Visual Grounding Dataset on City-scale Point Cloud Data
8. NeurIPS 2023Data Minimization at Inference Time
9. NeurIPS 2023Dataset Diffusion: Diffusion-based Synthetic Data Generation for Pixel-Level Semantic Segmentation
10. NeurIPS 2023DatasetDM: Synthesizing Data with Perception Annotations Using Diffusion Models
11. NeurIPS 2023Distributional Learning of Variational AutoEncoder: Application to Synthetic Data Generation
12. NeurIPS 2023Diverse Community Data for Benchmarking Data Privacy Algorithms
13. NeurIPS 2023Does Graph Distillation See Like Vision Dataset Counterpart?
14. NeurIPS 2023DreamSim: Learning New Dimensions of Human Visual Similarity using Synthetic Data
15. NeurIPS 2023Echoes Beyond Points: Unleashing the Power of Raw Radar Data in Multi-modality Fusion
16. NeurIPS 2023Expanding Small-Scale Datasets with Guided Imagination
17. NeurIPS 2023ExPT: Synthetic Pretraining for Few-Shot Experimental Design
18. NeurIPS 2023Few-shot Generation via Recalling Brain-Inspired Episodic-Semantic Memory
19. NeurIPS 2023Finding Order in Chaos: A Novel Data Augmentation Method for Time Series in Contrastive Learning
20. NeurIPS 2023GlucoSynth: Generating Differentially-Private Synthetic Glucose Traces
21. NeurIPS 2023Harnessing Hard Mixed Samples with Decoupled Regularizer
22. NeurIPS 2023Improving multimodal datasets with image captioning
23. NeurIPS 2023IPMix: Label-Preserving Data Augmentation Method for Training Robust Classifiers
24. NeurIPS 2023Joint Data-Task Generation for Auxiliary Learning
25. NeurIPS 2023Multi-resolution Spectral Coherence for Graph Generation with Score-based Diffusion
26. NeurIPS 2023Nearest Neighbour with Bandit Feedback
27. NeurIPS 2023NICE: NoIse-modulated Consistency rEgularization for Data-Efficient GANs
28. NeurIPS 2023On the Implicit Bias of Linear Equivariant Steerable Networks
29. NeurIPS 2023OpenDataVal: a Unified Benchmark for Data Valuation
30. NeurIPS 2023OpenProteinSet: Training data for structural biology at scale
31. NeurIPS 2023PCF-GAN: generating sequential data via the characteristic function of measures on the path space
32. NeurIPS 2023Post-processing Private Synthetic Data for Improving Utility on Selected Measures
33. NeurIPS 2023PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning
34. NeurIPS 2023Realistic Synthetic Financial Transactions for Anti-Money Laundering Models
35. NeurIPS 2023Reimagining Synthetic Tabular Data Generation through Data-Centric AI: A Comprehensive Benchmark
36. NeurIPS 2023Repetition In Repetition Out: Towards Understanding Neural Text Degeneration from the Data Perspective
37. NeurIPS 2023Revisit the Power of Vanilla Knowledge Distillation: from Small Scale to Large Scale
38. NeurIPS 2023Squeeze, Recover and Relabel: Dataset Condensation at ImageNet Scale From A New Perspective
39. NeurIPS 2023Synthcity: a benchmark framework for diverse use cases of tabular synthetic data
40. NeurIPS 2023Toward Understanding Generative Data Augmentation
41. NeurIPS 2023Trading-off price for data quality to achieve fair online allocation
42. NeurIPS 2023Triangulation Residual Loss for Data-efficient 3D Pose Estimation
43. NeurIPS 2023Understanding Diffusion Objectives as the ELBO with Simple Data Augmentation
44. NeurIPS 2023Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift
45. NeurIPS 2023VidChapters-7M: Video Chapters at Scale

FAQ

How many Synthetic Data Generation papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

277 in total: 72 in 2023, 41 in 2024, 68 in 2025, 96 in 2026.

How many Synthetic Data Generation papers are at NeurIPS 2026?

NeurIPS 2026 has 24 Synthetic Data Generation papers, versus 27 the year before.

How many Synthetic Data Generation papers are at ICLR 2026?

ICLR 2026 has 26 Synthetic Data Generation papers, versus 18 the year before.

How many Synthetic Data Generation papers are at ICML 2026?

ICML 2026 has 21 Synthetic Data Generation papers, versus 9 the year before.

How many Synthetic Data Generation papers are at CVPR 2026?

CVPR 2026 has 25 Synthetic Data Generation papers, versus 14 the year before.

Which conference publishes the most Synthetic Data Generation papers?

NeurIPS, with 114 papers from 2023 to 2026.