扩散模型论文趋势 2023–2026

主要结论

• 扩散模型论文从 2023 年的 660 篇增长到 2026 年的 2,691 篇，三年间扩大到约 4.1 倍。
• NeurIPS 是发扩散模型论文最多的会议，2023–2026 年共 2,202 篇，占四个会议总量的 32%。
• 交叉方向里涨得最快的是应用 · chemistry physics and earth sciences：同时属于两个主题的论文从 2023 年的 14 篇增至 2026 年的 163 篇。
• 在「深度学习」的 11 个主题里，它的 2026 年论文数排第 1；同组增长最快的深度学习 · foundation models是 2.5 倍，扩散模型是 4.1 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 2026$\mathbf{D^{3}S^{2}}$: Diffusion-Guided Dataset Distillation for Semantic Segmentation
• ICML 2026“Do Diffusion Models Dream of Electric Planes?” Discrete and Continuous Simulation-Based Inference for Aircraft Design
• ICLR 2026$\alpha$-DPO: Robust Preference Alignment for Diffusion Models via $\alpha$ Divergence
• CVPR 20262ndMatch Finetuning Pruned Diffusion Models via Second-Order Jacobian Matching
• NeurIPS 2025$\text{S}^2$Q-VDiT: Accurate Quantized Video Diffusion Transformer with Salient Data and Sparse Token Distillation
• ICML 2025A First-order Generative Bilevel Optimization Framework for Diffusion Models
• ICLR 2025$\text{I}^2\text{AM}$: Interpreting Image-to-Image Latent Diffusion Models via Bi-Attribution Maps
• CVPR 20253DEnhancer: Consistent Multi-View Diffusion for 3D Enhancement
• NeurIPS 2024$\text{Di}^2\text{Pose}$: Discrete Diffusion Model for Occluded 3D Human Pose Estimation
• ICML 2024A Dense Reward View on Aligning Text-to-Image Diffusion with Preference
• ICLR 2024$\infty$-Diff: Infinite Resolution Diffusion with Subsampled Mollified States
• CVPR 2024D^4: Dataset Distillation via Disentangled Diffusion Model
• NeurIPS 20233D molecule generation by denoising voxel grids
• ICML 2023A Critical Revisit of Adversarial Robustness in 3D Point Cloud Recognition with Diffusion-Driven Purification
• ICLR 2023(Certified!!) Adversarial Robustness for Free!
• CVPR 20233D Neural Field Generation Using Triplane Diffusion
• NeurIPS 2026$\text{PartConcepts}$: A Unified Mechanism for Fine-Grained Part Localization and Generation
• ICML 2026$\sigma$: Sigmoid Modulation for Ultra High Resolution Diffusion
• ICLR 2026$\textit{MADFormer}$: Mixed Autoregressive and Diffusion Transformers for Continuous Image Generation
• CVPR 20263D-LATTE Latent Space 3D Editing from Textual Instructions

全部扩散模型论文

共 109 篇，第 2 / 3 页

51. ICML 2023Improved Analysis of Score-based Generative Modeling: User-Friendly Bounds under Minimal Smoothness Assumptions
52. ICML 2023Improved Techniques for Maximum Likelihood Estimation for Diffusion ODEs
53. ICML 2023Improving Adversarial Robustness Through the Contrastive-Guided Diffusion Process
54. ICML 2023InfoDiffusion: Representation Learning Using Information Maximizing Diffusion Models
55. ICML 2023Input Perturbation Reduces Exposure Bias in Diffusion Models
56. ICML 2023KDEformer: Accelerating Transformers via Kernel Density Estimation
57. ICML 2023Learning to Jump: Thinning and Thickening Latent Counts for Generative Modeling
58. ICML 2023Long Horizon Temperature Scaling
59. ICML 2023Loss-Guided Diffusion Models for Plug-and-Play Controllable Generation
60. ICML 2023Make-An-Audio: Text-To-Audio Generation with Prompt-Enhanced Diffusion Models
61. ICML 2023MetaDiffuser: Diffusion Model as Conditional Planner for Offline Meta-RL
62. ICML 2023Minimizing Trajectory Curvature of ODE-based Generative Models
63. ICML 2023Modeling Temporal Data as Continuous Functions with Stochastic Process Diffusion
64. ICML 2023MolDiff: Addressing the Atom-Bond Inconsistency Problem in 3D Molecule Diffusion Generation
65. ICML 2023MultiDiffusion: Fusing Diffusion Paths for Controlled Image Generation
66. ICML 2023Multisample Flow Matching: Straightening Flows with Minibatch Couplings
67. ICML 2023NerfDiff: Single-image View Synthesis with NeRF-guided Distillation from 3D-aware Diffusion
68. ICML 2023Neural Diffusion Processes
69. ICML 2023Non-autoregressive Conditional Diffusion Models for Time Series Prediction
70. ICML 2023Nonparametric Generative Modeling with Conditional Sliced-Wasserstein Flows
71. ICML 2023OCD: Learning to Overfit with Conditional Diffusion Models
72. ICML 2023OMS-DPM: Optimizing the Model Schedule for Diffusion Probabilistic Models
73. ICML 2023On Investigating the Conservative Property of Score-Based Generative Models
74. ICML 2023On the Convergence of Gradient Flow on Multi-layer Linear Models
75. ICML 2023One Transformer Fits All Distributions in Multi-Modal Diffusion at Scale
76. ICML 2023Optimizing DDPM Sampling with Shortcut Fine-Tuning
77. ICML 2023PAC-Bayesian Generalization Bounds for Adversarial Generative Models
78. ICML 2023PFGM++: Unlocking the Potential of Physics-Inspired Generative Models
79. ICML 2023PixelAsParam: A Gradient View on Diffusion Sampling with Guidance
80. ICML 2023PLay: Parametrically Conditioned Layout Generation using Latent Diffusion
81. ICML 2023Q-Flow: Generative Modeling for Differential Equations of Open Quantum Dynamics with Normalizing Flows
82. ICML 2023Raising the Cost of Malicious AI-Powered Image Editing
83. ICML 2023ReDi: Efficient Learning-Free Diffusion Inference via Trajectory Retrieval
84. ICML 2023Reduce, Reuse, Recycle: Compositional Generation with Energy-Based Diffusion Models and MCMC
85. ICML 2023Refining Generative Process with Discriminator Guidance in Score-based Diffusion Models
86. ICML 2023Reflected Diffusion Models
87. ICML 2023Restoration based Generative Models
88. ICML 2023Restoration-Degradation Beyond Linear Diffusions: A Non-Asymptotic Analysis For DDIM-type Samplers
89. ICML 2023Revisiting Discriminative vs. Generative Classifiers: Theory and Implications
90. ICML 2023RLEG: Vision-Language Representation Learning with Diffusion-based Embedding Generation
91. ICML 2023Scalable Adaptive Computation for Iterative Generation
92. ICML 2023Score Approximation, Estimation and Distribution Recovery of Diffusion Models on Low-Dimensional Data
93. ICML 2023SDDM: Score-Decomposed Diffusion Models on Manifolds for Unpaired Image-to-Image Translation
94. ICML 2023SE(3) diffusion model with application to protein backbone generation
95. ICML 2023simple diffusion: End-to-end diffusion for high resolution images
96. ICML 2023SinDDM: A Single Image Denoising Diffusion Model
97. ICML 2023SinFusion: Training Diffusion Models on a Single Image or Video
98. ICML 2023SMURF-THP: Score Matching-based UnceRtainty quantiFication for Transformer Hawkes Process
99. ICML 2023StyleGAN-T: Unlocking the Power of GANs for Fast Large-Scale Text-to-Image Synthesis
100. ICML 2023Subset Selection Based On Multiple Rankings in the Presence of Bias: Effectiveness of Fairness Constraints for Multiwinner Voting Score Functions

常见问题

2023–2026 年四大会议一共有多少篇扩散模型论文？

共 6,900 篇，按年份分别是 2023 年 660 篇、2024 年 1,471 篇、2025 年 2,078 篇、2026 年 2,691 篇。

NeurIPS 2026 有多少篇扩散模型论文？

NeurIPS 2026 有 661 篇扩散模型论文，上一届是 694 篇。

ICLR 2026 有多少篇扩散模型论文？

ICLR 2026 有 694 篇扩散模型论文，上一届是 487 篇。

ICML 2026 有多少篇扩散模型论文？

ICML 2026 有 728 篇扩散模型论文，上一届是 346 篇。

CVPR 2026 有多少篇扩散模型论文？

CVPR 2026 有 608 篇扩散模型论文，上一届是 551 篇。

哪个会议的扩散模型论文最多？

NeurIPS，2023–2026 年共 2,202 篇。