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 660 篇，第 13 / 14 页
- NeurIPS 2023SE(3) Equivariant Augmented Coupling Flows
- NeurIPS 2023SEEDS: Exponential SDE Solvers for Fast High-Quality Sampling from Diffusion Models
- NeurIPS 2023SEGA: Instructing Text-to-Image Models using Semantic Guidance
- NeurIPS 2023SegRefiner: Towards Model-Agnostic Segmentation Refinement with Discrete Diffusion Process
- NeurIPS 2023Semi-Implicit Denoising Diffusion Models (SIDDMs)
- NeurIPS 2023SlotDiffusion: Object-Centric Generative Modeling with Diffusion Models
- NeurIPS 2023SnapFusion: Text-to-Image Diffusion Model on Mobile Devices within Two Seconds
- NeurIPS 2023Solving Inverse Physics Problems with Score Matching
- NeurIPS 2023Solving Linear Inverse Problems Provably via Posterior Sampling with Latent Diffusion Models
- NeurIPS 2023Spatio-Angular Convolutions for Super-resolution in Diffusion MRI
- NeurIPS 2023Spontaneous symmetry breaking in generative diffusion models
- NeurIPS 2023Stable Bias: Evaluating Societal Representations in Diffusion Models
- NeurIPS 2023Stable Diffusion is Unstable
- NeurIPS 2023Star-Shaped Denoising Diffusion Probabilistic Models
- NeurIPS 2023Strategic Behavior in Two-sided Matching Markets with Prediction-enhanced Preference-formation
- NeurIPS 2023Structural Pruning for Diffusion Models
- NeurIPS 2023StyleGAN knows Normal, Depth, Albedo, and More
- NeurIPS 2023StyleTTS 2: Towards Human-Level Text-to-Speech through Style Diffusion and Adversarial Training with Large Speech Language Models
- NeurIPS 2023Subject-driven Text-to-Image Generation via Apprenticeship Learning
- NeurIPS 2023Symbolic Discovery of Optimization Algorithms
- NeurIPS 2023SyncDiffusion: Coherent Montage via Synchronized Joint Diffusions
- NeurIPS 2023SynMob: Creating High-Fidelity Synthetic GPS Trajectory Dataset for Urban Mobility Analysis
- NeurIPS 2023Synthetic Experience Replay
- NeurIPS 2023T2T: From Distribution Learning in Training to Gradient Search in Testing for Combinatorial Optimization
- NeurIPS 2023Tanh Works Better with Asymmetry
- NeurIPS 2023Temporal Dynamic Quantization for Diffusion Models
- NeurIPS 2023Text-to-Image Diffusion Models are Zero Shot Classifiers
- NeurIPS 2023TextDiffuser: Diffusion Models as Text Painters
- NeurIPS 2023The CLIP Model is Secretly an Image-to-Prompt Converter
- NeurIPS 2023The probability flow ODE is provably fast
- NeurIPS 2023The Surprising Effectiveness of Diffusion Models for Optical Flow and Monocular Depth Estimation
- NeurIPS 2023TopP&R: Robust Support Estimation Approach for Evaluating Fidelity and Diversity in Generative Models
- NeurIPS 2023Towards Consistent Video Editing with Text-to-Image Diffusion Models
- NeurIPS 2023Towards Symmetry-Aware Generation of Periodic Materials
- NeurIPS 2023Towards Test-Time Refusals via Concept Negation
- NeurIPS 2023Training Energy-Based Normalizing Flow with Score-Matching Objectives
- NeurIPS 2023Training-free Diffusion Model Adaptation for Variable-Sized Text-to-Image Synthesis
- NeurIPS 2023Trans-Dimensional Generative Modeling via Jump Diffusion Models
- NeurIPS 2023Tree-Based Diffusion Schrödinger Bridge with Applications to Wasserstein Barycenters
- NeurIPS 2023Tree-Rings Watermarks: Invisible Fingerprints for Diffusion Images
- NeurIPS 2023TWIGMA: A dataset of AI-Generated Images with Metadata From Twitter
- NeurIPS 2023Uncertainty Quantification via Neural Posterior Principal Components
- NeurIPS 2023Understanding and Mitigating Copying in Diffusion Models
- NeurIPS 2023Understanding Diffusion Objectives as the ELBO with Simple Data Augmentation
- NeurIPS 2023Understanding the Latent Space of Diffusion Models through the Lens of Riemannian Geometry
- NeurIPS 2023Uni-ControlNet: All-in-One Control to Text-to-Image Diffusion Models
- NeurIPS 2023UniControl: A Unified Diffusion Model for Controllable Visual Generation In the Wild
- NeurIPS 2023Unifying GANs and Score-Based Diffusion as Generative Particle Models
- NeurIPS 2023Unifying Predictions of Deterministic and Stochastic Physics in Mesh-reduced Space with Sequential Flow Generative Model
- NeurIPS 2023UniPC: A Unified Predictor-Corrector Framework for Fast Sampling of Diffusion Models
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