合成数据生成论文趋势 2023–2026

主要结论

• 合成数据生成论文从 2023 年的 72 篇增长到 2026 年的 96 篇，三年间扩大到约 1.3 倍。
• NeurIPS 是发合成数据生成论文最多的会议，2023–2026 年共 114 篇，占四个会议总量的 41%。
• 交叉方向里涨得最快的是扩散模型：同时属于两个主题的论文从 2023 年的 6 篇增至 2026 年的 20 篇。
• 在「以数据为中心 AI」的 5 个主题里，它的 2026 年论文数排第 1；同组增长最快的弱监督是 1.3 倍，合成数据生成是 1.3 倍。

代表论文

按年份和会议均匀挑选，方便快速看到每一届的样貌

• 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

全部合成数据生成论文

共 72 篇，第 1 / 2 页

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

常见问题

2023–2026 年四大会议一共有多少篇合成数据生成论文？

共 277 篇，按年份分别是 2023 年 72 篇、2024 年 41 篇、2025 年 68 篇、2026 年 96 篇。

NeurIPS 2026 有多少篇合成数据生成论文？

NeurIPS 2026 有 24 篇合成数据生成论文，上一届是 27 篇。

ICLR 2026 有多少篇合成数据生成论文？

ICLR 2026 有 26 篇合成数据生成论文，上一届是 18 篇。

ICML 2026 有多少篇合成数据生成论文？

ICML 2026 有 21 篇合成数据生成论文，上一届是 9 篇。

CVPR 2026 有多少篇合成数据生成论文？

CVPR 2026 有 25 篇合成数据生成论文，上一届是 14 篇。

哪个会议的合成数据生成论文最多？

NeurIPS，2023–2026 年共 114 篇。