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 55 篇，第 1 / 2 页

1. ICLR 2026AgentSynth: Scalable Task Generation for Generalist Computer-Use Agents
2. ICLR 2026Critic–Adviser–Reviser Cyclic Refinement: Towards High-Quality EMR Corpus Generation with LLMs
3. ICLR 2026Decoupled DMD: CFG Augmentation as the Spear, Distribution Matching as the Shield
4. ICLR 2026Discrete Bayesian Sample Inference for Graph Generation
5. ICLR 2026Do We Need All the Synthetic Data? Targeted Image Augmentation via Diffusion Models
6. ICLR 2026Evolutionary Caching to Accelerate Your Off-the-Shelf Diffusion Model
7. ICLR 2026Exploring Synthesizable Chemical Space with Iterative Pathway Refinements
8. ICLR 2026GraphUniverse: Enabling Systematic Evaluation of Inductive Generalization
9. ICLR 2026High-dimensional Analysis of Synthetic Data Selection
10. ICLR 2026Latent-to-Data Cascaded Diffusion Models for Unconditional Time Series Generation
11. ICLR 2026Learning Posterior Predictive Distributions for Node Classification from Synthetic Graph Priors
12. ICLR 2026Making, Not Taking, the Best of N
13. ICLR 2026Neon: Negative Extrapolation From Self-Training Improves Image Generation
14. ICLR 2026OptimSyn: Influence-Guided Rubrics Optimization for Synthetic Data Generation
15. ICLR 2026Reformulation for Pretraining Data Augmentation
16. ICLR 2026ReLaSH: Reconstructing Joint Latent Spaces for Efficient Generation of Synthetic Hypergraphs with Hyperlink Attributes
17. ICLR 2026Rethinking Driving World Model as Synthetic Data Generator for Perception Tasks
18. ICLR 2026SAIR: Enabling Deep Learning for Protein-Ligand Interactions with a Synthetic Structural Dataset
19. ICLR 2026Scaling Synthetic Task Generation for Agents via Exploration
20. ICLR 2026Secret-Protected Evolution for Differentially Private Synthetic Text Generation
21. ICLR 2026SIPDO: Closed-Loop Prompt Optimization via Synthetic Data Feedback
22. ICLR 2026SMOTE and Mirrors: Exposing Privacy Leakage from Synthetic Minority Oversampling
23. ICLR 2026Source-Guided Flow Matching
24. ICLR 2026Synthetic Bootstrapped Pretraining
25. ICLR 2026TabStruct: Measuring Structural Fidelity of Tabular Data
26. ICLR 2026Using maximal information auxiliary variables to improve synthetic data generation based on TabPFN foundation models
27. ICLR 2025API Pack: A Massive Multi-Programming Language Dataset for API Call Generation
28. ICLR 2025Beyond the convexity assumption: Realistic tabular data generation under quantifier-free real linear constraints
29. ICLR 2025Conditional Diffusion with Ordinal Regression: Longitudinal Data Generation for Neurodegenerative Disease Studies
30. ICLR 2025Continuous Diffusion for Mixed-Type Tabular Data
31. ICLR 2025CraftRTL: High-quality Synthetic Data Generation for Verilog Code Models with Correct-by-Construction Non-Textual Representations and Targeted Code Repair
32. ICLR 2025CTSyn: A Foundation Model for Cross Tabular Data Generation
33. ICLR 2025DataEnvGym: Data Generation Agents in Teacher Environments with Student Feedback
34. ICLR 2025DataGen: Unified Synthetic Dataset Generation via Large Language Models
35. ICLR 2025Fictitious Synthetic Data Can Improve LLM Factuality via Prerequisite Learning
36. ICLR 2025Gaussian Mixture Counterfactual Generator
37. ICLR 2025MindSimulator: Exploring Brain Concept Localization via Synthetic fMRI
38. ICLR 2025Personalized Representation from Personalized Generation
39. ICLR 2025Scaling Instruction-tuned LLMs to Million-token Contexts via Hierarchical Synthetic Data Generation
40. ICLR 2025Single Teacher, Multiple Perspectives: Teacher Knowledge Augmentation for Enhanced Knowledge Distillation
41. ICLR 2025Synthetic continued pretraining
42. ICLR 2025The Power of LLM-Generated Synthetic Data for Stance Detection in Online Political Discussions
43. ICLR 2025Towards a Theoretical Understanding of Synthetic Data in LLM Post-Training: A Reverse-Bottleneck Perspective
44. ICLR 2025Vec2Face: Scaling Face Dataset Generation with Loosely Constrained Vectors
45. ICLR 2024A Linear Algebraic Framework for Counterfactual Generation
46. ICLR 2024Achieving Human Parity in Content-Grounded Datasets Generation
47. ICLR 2024Diffusion-TS: Interpretable Diffusion for General Time Series Generation
48. ICLR 2024How Realistic Is Your Synthetic Data? Constraining Deep Generative Models for Tabular Data
49. ICLR 2024LLM-Assisted Code Cleaning For Training Accurate Code Generators
50. ICLR 2024Teaching Language Models to Hallucinate Less with Synthetic Tasks

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。