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 2 / 3 页

51. NeurIPS 2025Towards Syn-to-Real IQA: A Novel Perspective on Reshaping Synthetic Data Distributions
52. NeurIPS 2024$\text{ID}^3$: Identity-Preserving-yet-Diversified Diffusion Models for Synthetic Face Recognition
53. NeurIPS 2024A Label is Worth A Thousand Images in Dataset Distillation
54. NeurIPS 2024CemiFace: Center-based Semi-hard Synthetic Face Generation for Face Recognition
55. NeurIPS 2024Dealing with Synthetic Data Contamination in Online Continual Learning
56. NeurIPS 2024Debiasing Synthetic Data Generated by Deep Generative Models
57. NeurIPS 2024DECO-Bench: Unified Benchmark for Decoupled Task-Agnostic Synthetic Data Release
58. NeurIPS 2024DiffAug: A Diffuse-and-Denoise Augmentation for Training Robust Classifiers
59. NeurIPS 2024FairWire: Fair Graph Generation
60. NeurIPS 2024HardCore Generation: Generating Hard UNSAT Problems for Data Augmentation
61. NeurIPS 2024High Rank Path Development: an approach to learning the filtration of stochastic processes
62. NeurIPS 2024Hints-In-Browser: Benchmarking Language Models for Programming Feedback Generation
63. NeurIPS 2024On the Ability of Developers' Training Data Preservation of Learnware
64. NeurIPS 2024Privacy without Noisy Gradients: Slicing Mechanism for Generative Model Training
65. NeurIPS 2024SimGen: Simulator-conditioned Driving Scene Generation
66. NeurIPS 2024SynRS3D: A Synthetic Dataset for Global 3D Semantic Understanding from Monocular Remote Sensing Imagery
67. NeurIPS 2024Synthesize, Partition, then Adapt: Eliciting Diverse Samples from Foundation Models
68. NeurIPS 2024TabEBM: A Tabular Data Augmentation Method with Distinct Class-Specific Energy-Based Models
69. NeurIPS 2024TSGM: A Flexible Framework for Generative Modeling of Synthetic Time Series
70. NeurIPS 2023[Re] $\mathcal{G}$-Mixup: Graph Data Augmentation for Graph Classification
71. NeurIPS 20234D Panoptic Scene Graph Generation
72. NeurIPS 2023Adaptive Principal Component Regression with Applications to Panel Data
73. NeurIPS 2023Back-Modality: Leveraging Modal Transformation for Data Augmentation
74. NeurIPS 2023Benchmarking Distribution Shift in Tabular Data with TableShift
75. NeurIPS 2023Can You Rely on Your Model Evaluation? Improving Model Evaluation with Synthetic Test Data
76. NeurIPS 2023CityRefer: Geography-aware 3D Visual Grounding Dataset on City-scale Point Cloud Data
77. NeurIPS 2023Data Minimization at Inference Time
78. NeurIPS 2023Dataset Diffusion: Diffusion-based Synthetic Data Generation for Pixel-Level Semantic Segmentation
79. NeurIPS 2023DatasetDM: Synthesizing Data with Perception Annotations Using Diffusion Models
80. NeurIPS 2023Distributional Learning of Variational AutoEncoder: Application to Synthetic Data Generation
81. NeurIPS 2023Diverse Community Data for Benchmarking Data Privacy Algorithms
82. NeurIPS 2023Does Graph Distillation See Like Vision Dataset Counterpart?
83. NeurIPS 2023DreamSim: Learning New Dimensions of Human Visual Similarity using Synthetic Data
84. NeurIPS 2023Echoes Beyond Points: Unleashing the Power of Raw Radar Data in Multi-modality Fusion
85. NeurIPS 2023Expanding Small-Scale Datasets with Guided Imagination
86. NeurIPS 2023ExPT: Synthetic Pretraining for Few-Shot Experimental Design
87. NeurIPS 2023Few-shot Generation via Recalling Brain-Inspired Episodic-Semantic Memory
88. NeurIPS 2023Finding Order in Chaos: A Novel Data Augmentation Method for Time Series in Contrastive Learning
89. NeurIPS 2023GlucoSynth: Generating Differentially-Private Synthetic Glucose Traces
90. NeurIPS 2023Harnessing Hard Mixed Samples with Decoupled Regularizer
91. NeurIPS 2023Improving multimodal datasets with image captioning
92. NeurIPS 2023IPMix: Label-Preserving Data Augmentation Method for Training Robust Classifiers
93. NeurIPS 2023Joint Data-Task Generation for Auxiliary Learning
94. NeurIPS 2023Multi-resolution Spectral Coherence for Graph Generation with Score-based Diffusion
95. NeurIPS 2023Nearest Neighbour with Bandit Feedback
96. NeurIPS 2023NICE: NoIse-modulated Consistency rEgularization for Data-Efficient GANs
97. NeurIPS 2023On the Implicit Bias of Linear Equivariant Steerable Networks
98. NeurIPS 2023OpenDataVal: a Unified Benchmark for Data Valuation
99. NeurIPS 2023OpenProteinSet: Training data for structural biology at scale
100. NeurIPS 2023PCF-GAN: generating sequential data via the characteristic function of measures on the path space

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。