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

277 papers, page 4 of 6

151. NeurIPS 2025MIDAS: Misalignment-based Data Augmentation Strategy for Imbalanced Multimodal Learning
152. NeurIPS 2025MoleBridge: Synthetic Space Projecting with Discrete Markov Bridges
153. NeurIPS 2025Non-Adaptive Adversarial Face Generation
154. NeurIPS 2025PANGEA: Projection-Based Augmentation with Non-Relevant General Data for Enhanced Domain Adaptation in LLMs
155. NeurIPS 2025Parameterized Synthetic Text Generation with SimpleStories
156. NeurIPS 2025Private Evolution Converges
157. NeurIPS 2025ROSE: Remove Objects with Side Effects in Videos
158. NeurIPS 2025Seeing What Matters: Generalizable AI-generated Video Detection with Forensic-Oriented Augmentation
159. NeurIPS 2025Self-Adapting Language Models
160. NeurIPS 2025SimpleStrat: Diversifying Language Model Generation with Stratification
161. NeurIPS 2025Spend Wisely: Maximizing Post-Training Gains in Iterative Synthetic Data Bootstrapping
162. NeurIPS 2025Synthetic Series-Symbol Data Generation for Time Series Foundation Models
163. NeurIPS 2025Thousand Voices of Trauma: A Large-Scale Synthetic Dataset for Modeling Prolonged Exposure Therapy Conversations
164. NeurIPS 2025Towards Syn-to-Real IQA: A Novel Perspective on Reshaping Synthetic Data Distributions
165. CVPR 2024Density-guided Translator Boosts Synthetic-to-Real Unsupervised Domain Adaptive Segmentation of 3D Point Clouds
166. CVPR 2024Design2Cloth: 3D Cloth Generation from 2D Masks
167. CVPR 2024DiffuseMix: Label-Preserving Data Augmentation with Diffusion Models
168. CVPR 2024EgoGen: An Egocentric Synthetic Data Generator
169. CVPR 2024FairRAG: Fair Human Generation via Fair Retrieval Augmentation
170. CVPR 2024Learning from Synthetic Human Group Activities
171. CVPR 2024SemCity: Semantic Scene Generation with Triplane Diffusion
172. CVPR 2024WinSyn: : A High Resolution Testbed for Synthetic Data
173. ICLR 2024A Linear Algebraic Framework for Counterfactual Generation
174. ICLR 2024Achieving Human Parity in Content-Grounded Datasets Generation
175. ICLR 2024Diffusion-TS: Interpretable Diffusion for General Time Series Generation
176. ICLR 2024How Realistic Is Your Synthetic Data? Constraining Deep Generative Models for Tabular Data
177. ICLR 2024LLM-Assisted Code Cleaning For Training Accurate Code Generators
178. ICLR 2024Teaching Language Models to Hallucinate Less with Synthetic Tasks
179. ICML 2024CaPS: Collaborative and Private Synthetic Data Generation from Distributed Sources
180. ICML 2024CaRiNG: Learning Temporal Causal Representation under Non-Invertible Generation Process
181. ICML 2024Compositional Capabilities of Autoregressive Transformers: A Study on Synthetic, Interpretable Tasks
182. ICML 2024CuTS: Customizable Tabular Synthetic Data Generation
183. ICML 2024Differentially Private Sum-Product Networks
184. ICML 2024Leverage Class-Specific Accuracy to Guide Data Generation for Improving Image Classification
185. ICML 2024Magicoder: Empowering Code Generation with OSS-Instruct
186. ICML 2024MILP-FBGen: LP/MILP Instance Generation with Feasibility/Boundedness
187. ICML 2024Sharpness-Aware Data Generation for Zero-shot Quantization
188. NeurIPS 2024$\text{ID}^3$: Identity-Preserving-yet-Diversified Diffusion Models for Synthetic Face Recognition
189. NeurIPS 2024A Label is Worth A Thousand Images in Dataset Distillation
190. NeurIPS 2024CemiFace: Center-based Semi-hard Synthetic Face Generation for Face Recognition
191. NeurIPS 2024Dealing with Synthetic Data Contamination in Online Continual Learning
192. NeurIPS 2024Debiasing Synthetic Data Generated by Deep Generative Models
193. NeurIPS 2024DECO-Bench: Unified Benchmark for Decoupled Task-Agnostic Synthetic Data Release
194. NeurIPS 2024DiffAug: A Diffuse-and-Denoise Augmentation for Training Robust Classifiers
195. NeurIPS 2024FairWire: Fair Graph Generation
196. NeurIPS 2024HardCore Generation: Generating Hard UNSAT Problems for Data Augmentation
197. NeurIPS 2024High Rank Path Development: an approach to learning the filtration of stochastic processes
198. NeurIPS 2024Hints-In-Browser: Benchmarking Language Models for Programming Feedback Generation
199. NeurIPS 2024On the Ability of Developers' Training Data Preservation of Learnware
200. NeurIPS 2024Privacy without Noisy Gradients: Slicing Mechanism for Generative Model Training

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.