Synthetic Data Generation papers, 2023–2026
Data augmentation at scale
Scope: NeurIPS, ICLR, ICML and CVPR, 2023–2026. 277 papers are tagged with this topic.
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.
Papers per venue
Counts by year and venue
| Year | NeurIPS | ICLR | ICML | CVPR | Total |
|---|---|---|---|---|---|
| 2023 | 45 | 5 | 13 | 9 | 72 |
| 2024 | 18 | 6 | 9 | 8 | 41 |
| 2025 | 27 | 18 | 9 | 14 | 68 |
| 2026 | 24 | 26 | 21 | 25 | 96 |
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
72 papers, page 1 of 2
- CVPR 2023BEDLAM: A Synthetic Dataset of Bodies Exhibiting Detailed Lifelike Animated Motion
- CVPR 2023DCFace: Synthetic Face Generation With Dual Condition Diffusion Model
- CVPR 2023Exploring Incompatible Knowledge Transfer in Few-Shot Image Generation
- CVPR 2023Fake It Till You Make It: Learning Transferable Representations From Synthetic ImageNet Clones
- CVPR 2023Fast Contextual Scene Graph Generation With Unbiased Context Augmentation
- CVPR 2023HandsOff: Labeled Dataset Generation With No Additional Human Annotations
- CVPR 2023MIME: Human-Aware 3D Scene Generation
- CVPR 2023PixHt-Lab: Pixel Height Based Light Effect Generation for Image Compositing
- CVPR 2023Swept-Angle Synthetic Wavelength Interferometry
- ICLR 2023DFlow: Learning to Synthesize Better Optical Flow Datasets via a Differentiable Pipeline
- ICLR 2023ILA-DA: Improving Transferability of Intermediate Level Attack with Data Augmentation
- ICLR 2023IS SYNTHETIC DATA FROM GENERATIVE MODELS READY FOR IMAGE RECOGNITION?
- ICLR 2023Learning with Stochastic Orders
- ICLR 2023Synthetic Data Generation of Many-to-Many Datasets via Random Graph Generation
- ICML 2023Adaptively Weighted Data Augmentation Consistency Regularization for Robust Optimization under Concept Shift
- ICML 2023Beam Tree Recursive Cells
- ICML 2023Conformal Prediction with Missing Values
- ICML 2023Data Feedback Loops: Model-driven Amplification of Dataset Biases
- ICML 2023Generating Private Synthetic Data with Genetic Algorithms
- ICML 2023Gradient-Free Structured Pruning with Unlabeled Data
- ICML 2023Improving Graph Generation by Restricting Graph Bandwidth
- ICML 2023OpenFE: Automated Feature Generation with Expert-level Performance
- ICML 2023Scalable Adaptive Computation for Iterative Generation
- ICML 2023Synthetic data for model selection
- ICML 2023Synthetic Data, Real Errors: How (Not) to Publish and Use Synthetic Data
- ICML 2023The Value of Out-of-Distribution Data
- ICML 2023Training Normalizing Flows from Dependent Data
- NeurIPS 2023[Re] $\mathcal{G}$-Mixup: Graph Data Augmentation for Graph Classification
- NeurIPS 20234D Panoptic Scene Graph Generation
- NeurIPS 2023Adaptive Principal Component Regression with Applications to Panel Data
- NeurIPS 2023Back-Modality: Leveraging Modal Transformation for Data Augmentation
- NeurIPS 2023Benchmarking Distribution Shift in Tabular Data with TableShift
- NeurIPS 2023Can You Rely on Your Model Evaluation? Improving Model Evaluation with Synthetic Test Data
- NeurIPS 2023CityRefer: Geography-aware 3D Visual Grounding Dataset on City-scale Point Cloud Data
- NeurIPS 2023Data Minimization at Inference Time
- NeurIPS 2023Dataset Diffusion: Diffusion-based Synthetic Data Generation for Pixel-Level Semantic Segmentation
- NeurIPS 2023DatasetDM: Synthesizing Data with Perception Annotations Using Diffusion Models
- NeurIPS 2023Distributional Learning of Variational AutoEncoder: Application to Synthetic Data Generation
- NeurIPS 2023Diverse Community Data for Benchmarking Data Privacy Algorithms
- NeurIPS 2023Does Graph Distillation See Like Vision Dataset Counterpart?
- NeurIPS 2023DreamSim: Learning New Dimensions of Human Visual Similarity using Synthetic Data
- NeurIPS 2023Echoes Beyond Points: Unleashing the Power of Raw Radar Data in Multi-modality Fusion
- NeurIPS 2023Expanding Small-Scale Datasets with Guided Imagination
- NeurIPS 2023ExPT: Synthetic Pretraining for Few-Shot Experimental Design
- NeurIPS 2023Few-shot Generation via Recalling Brain-Inspired Episodic-Semantic Memory
- NeurIPS 2023Finding Order in Chaos: A Novel Data Augmentation Method for Time Series in Contrastive Learning
- NeurIPS 2023GlucoSynth: Generating Differentially-Private Synthetic Glucose Traces
- NeurIPS 2023Harnessing Hard Mixed Samples with Decoupled Regularizer
- NeurIPS 2023Improving multimodal datasets with image captioning
- NeurIPS 2023IPMix: Label-Preserving Data Augmentation Method for Training Robust Classifiers
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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.