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 114 篇，第 1 / 3 页

1. NeurIPS 2026Breaking the Quality–Privacy Tradeoff in Tabular Data Generation via In-Context Learning
2. NeurIPS 2026DRTriton: Large-Scale Synthetic Data Driven Reinforcement Learning for Triton Kernel Generation
3. NeurIPS 2026EvoCUA: Evolving Computer Use Agents via Learning from Scalable Synthetic Experience
4. NeurIPS 2026Firefly: Illuminating Verified Real-world Tool Call Data Generation
5. NeurIPS 2026HELICS: Biobank-scale Conditional Synthetic Genome Generation via Latent Flow Matching
6. NeurIPS 2026How Data Augmentation Shapes Neural Representations
7. NeurIPS 2026InvestigationWorlds: An Agentic Environment for Legal Investigation
8. NeurIPS 2026Is Backpropagation Optimal? When Synthetic Gradients Improve Sample Efficiency
9. NeurIPS 2026L2P: Unlocking Latent Potential for Pixel Generation
10. NeurIPS 2026Learning with Synthetic Data via SGD in High-Dimensional Linear Regression
11. NeurIPS 2026OopsWorld! Operation-Grounded Seamless World Generation
12. NeurIPS 2026Persona Generators: Generating Diverse Synthetic Personas for Arbitrary Contexts
13. NeurIPS 2026Positive-Unlabeled Preference Optimization For Chest X-ray Report Generation
14. NeurIPS 2026Quest: Training Frontier Deep Research Agents with Fully Synthetic Tasks
15. NeurIPS 2026Risk-guided Estimation-aware Acceptance for Learning with Synthetic Data
16. NeurIPS 2026ScrapeGraphAI-100k: Dataset for Schema-Constrained LLM Generation
17. NeurIPS 2026SLS-Bench: A Benchmark for Incident Log Summarization with Synthetic Observability Data
18. NeurIPS 2026StereoPep: Do Molecular Models Understand Stereochemistry? A Benchmark on Synthetic Diastereomeric Peptides
19. NeurIPS 2026Synthon Contrastive Learning for Synthesizable 3D Molecule Generation
20. NeurIPS 2026TailDiff: Elicitable Tail-Guided Diffusion for Risk-Sensitive Generation
21. NeurIPS 2026Targeted Synthetic Control Method
22. NeurIPS 2026TempoPFN: Synthetic Pre-training of Linear RNNs for Zero-shot Time Series Forecasting
23. NeurIPS 2026Transcoda: End-to-End Zero-Shot Optical Music Recognition via Data-Centric Synthetic Training
24. NeurIPS 2026Transformers Converge to Invariant Algorithmic Cores
25. NeurIPS 2025Achilles' Heel of Mamba: Essential difficulties of the Mamba architecture demonstrated by synthetic data
26. NeurIPS 2025Amortized Active Generation of Pareto Sets
27. NeurIPS 2025AR-RAG: Autoregressive Retrieval Augmentation for Image Generation
28. NeurIPS 2025AugGen: Synthetic Augmentation using Diffusion Models Can Improve Recognition
29. NeurIPS 2025ChemOrch: Empowering LLMs with Chemical Intelligence via Groundbreaking Synthetic Instructions
30. NeurIPS 2025Constrained Posterior Sampling: Time Series Generation with Hard Constraints
31. NeurIPS 2025Diffusing DeBias: Synthetic Bias Amplification for Model Debiasing
32. NeurIPS 2025FerretNet: Efficient Synthetic Image Detection via Local Pixel Dependencies
33. NeurIPS 2025Forging Time Series with Language: A Large Language Model Approach to Synthetic Data Generation
34. NeurIPS 2025Improving the Generation and Evaluation of Synthetic Data for Downstream Medical Causal Inference
35. NeurIPS 2025Increasing the Utility of Synthetic Images through Chamfer Guidance
36. NeurIPS 2025KGGen: Extracting Knowledge Graphs from Plain Text with Language Models
37. NeurIPS 2025MesaTask: Towards Task-Driven Tabletop Scene Generation via 3D Spatial Reasoning
38. NeurIPS 2025MIDAS: Misalignment-based Data Augmentation Strategy for Imbalanced Multimodal Learning
39. NeurIPS 2025MoleBridge: Synthetic Space Projecting with Discrete Markov Bridges
40. NeurIPS 2025Non-Adaptive Adversarial Face Generation
41. NeurIPS 2025PANGEA: Projection-Based Augmentation with Non-Relevant General Data for Enhanced Domain Adaptation in LLMs
42. NeurIPS 2025Parameterized Synthetic Text Generation with SimpleStories
43. NeurIPS 2025Private Evolution Converges
44. NeurIPS 2025ROSE: Remove Objects with Side Effects in Videos
45. NeurIPS 2025Seeing What Matters: Generalizable AI-generated Video Detection with Forensic-Oriented Augmentation
46. NeurIPS 2025Self-Adapting Language Models
47. NeurIPS 2025SimpleStrat: Diversifying Language Model Generation with Stratification
48. NeurIPS 2025Spend Wisely: Maximizing Post-Training Gains in Iterative Synthetic Data Bootstrapping
49. NeurIPS 2025Synthetic Series-Symbol Data Generation for Time Series Foundation Models
50. NeurIPS 2025Thousand Voices of Trauma: A Large-Scale Synthetic Dataset for Modeling Prolonged Exposure Therapy Conversations

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。