扩散模型论文趋势 2023–2026
扩散、flow matching 与 score-based 生成
统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 6,900 篇被归入该主题的论文。
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。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 327 | 86 | 109 | 138 | 660 |
| 2024 | 520 | 260 | 195 | 496 | 1,471 |
| 2025 | 694 | 487 | 346 | 551 | 2,078 |
| 2026 | 661 | 694 | 728 | 608 | 2,691 |
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 2,078 篇，第 31 / 42 页
- NeurIPS 2025D-VST: Diffusion Transformer for Pathology-Correct Tone-Controllable Cross-Dye Virtual Staining of Whole Slide Images
- NeurIPS 2025d1: Scaling Reasoning in Diffusion Large Language Models via Reinforcement Learning
- NeurIPS 2025DCI: Dual-Conditional Inversion for Boosting Diffusion-Based Image Editing
- NeurIPS 2025DEAL: Diffusion Evolution Adversarial Learning for Sim-to-Real Transfer
- NeurIPS 2025DeblurDiff: Real-Word Image Deblurring with Generative Diffusion Models
- NeurIPS 2025Decomposing stimulus-specific sensory neural information via diffusion models
- NeurIPS 2025Deep Compositional Phase Diffusion for Long Motion Sequence Generation
- NeurIPS 2025Deep learning for continuous-time stochastic control with jumps
- NeurIPS 2025Denoising Trajectory Biases for Zero-Shot AI-Generated Image Detection
- NeurIPS 2025DenseDPO: Fine-Grained Temporal Preference Optimization for Video Diffusion Models
- NeurIPS 2025Derivative-Free Guidance in Continuous and Discrete Diffusion Models with Soft Value-based Decoding
- NeurIPS 2025DEXTER: Diffusion-Guided EXplanations with TExtual Reasoning for Vision Models
- NeurIPS 2025DGSolver: Diffusion Generalist Solver with Universal Posterior Sampling for Image Restoration
- NeurIPS 2025DICEPTION: A Generalist Diffusion Model for Visual Perceptual Tasks
- NeurIPS 2025DiCo: Revitalizing ConvNets for Scalable and Efficient Diffusion Modeling
- NeurIPS 2025Diff-ICMH: Harmonizing Machine and Human Vision in Image Compression with Generative Prior
- NeurIPS 2025DiffBreak: Is Diffusion-Based Purification Robust?
- NeurIPS 2025DiffE2E: Rethinking End-to-End Driving with a Hybrid Diffusion-Regression-Classification Policy
- NeurIPS 2025Differentiable Generalized Sliced Wasserstein Plans
- NeurIPS 2025DiffEye: Diffusion-Based Continuous Eye-Tracking Data Generation Conditioned on Natural Images
- NeurIPS 2025DiffLiG: Diffusion-enhanced Liquid Graph with Attention Propagation for Grid-to-Station Precipitation Correction
- NeurIPS 2025Diffusing DeBias: Synthetic Bias Amplification for Model Debiasing
- NeurIPS 2025Diffusion Adaptive Text Embedding for Text-to-Image Diffusion Models
- NeurIPS 2025Diffusion Beats Autoregressive in Data-Constrained Settings
- NeurIPS 2025Diffusion Classifiers Understand Compositionality, but Conditions Apply
- NeurIPS 2025Diffusion Feature Field for Text-based 3D Editing with Gaussian Splatting
- NeurIPS 2025Diffusion Federated Dataset
- NeurIPS 2025Diffusion Generative Modeling on Lie Group Representations
- NeurIPS 2025Diffusion Guided Adversarial State Perturbations in Reinforcement Learning
- NeurIPS 2025Diffusion Model as a Noise-Aware Latent Reward Model for Step-Level Preference Optimization
- NeurIPS 2025Diffusion Models and the Manifold Hypothesis: Log-Domain Smoothing is Geometry Adaptive
- NeurIPS 2025Diffusion Models Meet Contextual Bandits
- NeurIPS 2025Diffusion on Demand: Selective Caching and Modulation for Efficient Generation
- NeurIPS 2025Diffusion Transformers as Open-World Spatiotemporal Foundation Models
- NeurIPS 2025Diffusion Transformers for Imputation: Statistical Efficiency and Uncertainty Quantification
- NeurIPS 2025Diffusion Tree Sampling: Scalable inference‑time alignment of diffusion models
- NeurIPS 2025Diffusion-Based Hierarchical Graph Neural Networks for Simulating Nonlinear Solid Mechanics
- NeurIPS 2025Diffusion-Classifier Synergy: Reward-Aligned Learning via Mutual Boosting Loop for FSCIL
- NeurIPS 2025Diffusion-Driven Progressive Target Manipulation for Source-Free Domain Adaptation
- NeurIPS 2025Diffusion-Driven Two-Stage Active Learning for Low-Budget Semantic Segmentation
- NeurIPS 2025Diffusion-Guided Graph Data Augmentation
- NeurIPS 2025Dimension-free Score Matching and Time Bootstrapping for Diffusion Models
- NeurIPS 2025DINGO: Constrained Inference for Diffusion LLMs
- NeurIPS 2025DIPO: Dual-State Images Controlled Articulated Object Generation Powered by Diverse Data
- NeurIPS 2025Direct3D-S2: Gigascale 3D Generation Made Easy with Spatial Sparse Attention
- NeurIPS 2025DISCO: DISCrete nOise for Conditional Control in Text-to-Image Diffusion Models
- NeurIPS 2025Discovering Latent Graphs with GFlowNets for Diverse Conditional Image Generation
- NeurIPS 2025Discrete Diffusion Models: Novel Analysis and New Sampler Guarantees
- NeurIPS 2025Discrete Neural Flow Samplers with Locally Equivariant Transformer
- NeurIPS 2025Discrete Spatial Diffusion: Intensity-Preserving Diffusion Modeling
在 Claude、Cursor 里直接问这个趋势
接上 Paperlist MCP 后，写综述、挑方向或准备投稿时，不用离开对话框就能拿到这页的数字：每年各会议的论文数、增长倍数、涨得最快的子方向和代表论文，AI 会按你的问题整理。
可以直接复制这句话问 AI
用 paperlist 查扩散模型在 NeurIPS 2023–2026 的论文趋势，哪一年涨得最快？
AI 会调用的工具：get_topic_stats {"topic": "diffusion-models"}
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。
「深度学习」下的其他主题
- 深度学习 · generative models and autoencoders 4,314
- 深度学习 · large language models 2,334
- 深度学习 · self supervised learning 1,958
- 深度学习 · graph neural networks 1,648
- 深度学习 · optimization 953
- 深度学习 · representation learning 802
- 深度学习 · probabilistic methods 637
- 深度学习 · foundation models 536
- 深度学习 · causal inference 316
- 深度学习 · transfer learning 197