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 1,378 篇，第 20 / 28 页
- ICML 2025OmiAD: One-Step Adaptive Masked Diffusion Model for Multi-class Anomaly Detection via Adversarial Distillation
- ICML 2025On the Guidance of Flow Matching
- ICML 2025One Diffusion Step to Real-World Super-Resolution via Flow Trajectory Distillation
- ICML 2025One Image is Worth a Thousand Words: A Usability Preservable Text-Image Collaborative Erasing Framework
- ICML 2025One-Shot Heterogeneous Federated Learning with Local Model-Guided Diffusion Models
- ICML 2025One-Step Diffusion Policy: Fast Visuomotor Policies via Diffusion Distillation
- ICML 2025Open Materials Generation with Stochastic Interpolants
- ICML 2025Origin Identification for Text-Guided Image-to-Image Diffusion Models
- ICML 2025Outlier-Aware Post-Training Quantization for Discrete Graph Diffusion Models
- ICML 2025Outsourced Diffusion Sampling: Efficient Posterior Inference in Latent Spaces of Generative Models
- ICML 2025Parallel Simulation for Log-concave Sampling and Score-based Diffusion Models
- ICML 2025PCEvolve: Private Contrastive Evolution for Synthetic Dataset Generation via Few-Shot Private Data and Generative APIs
- ICML 2025PepTune: De Novo Generation of Therapeutic Peptides with Multi-Objective-Guided Discrete Diffusion
- ICML 2025Physics-Informed DeepONets for drift-diffusion on metric graphs: simulation and parameter identification
- ICML 2025PISA Experiments: Exploring Physics Post-Training for Video Diffusion Models by Watching Stuff Drop
- ICML 2025Playmate: Flexible Control of Portrait Animation via 3D-Implicit Space Guided Diffusion
- ICML 2025PolyConf: Unlocking Polymer Conformation Generation through Hierarchical Generative Models
- ICML 2025Posterior Inference with Diffusion Models for High-dimensional Black-box Optimization
- ICML 2025PPDiff: Diffusing in Hybrid Sequence-Structure Space for Protein-Protein Complex Design
- ICML 2025Preference Adaptive and Sequential Text-to-Image Generation
- ICML 2025Prior Knowledge Guided Neural Architecture Generation
- ICML 2025Privacy Attacks on Image AutoRegressive Models
- ICML 2025ProDiff: Prototype-Guided Diffusion for Minimal Information Trajectory Imputation
- ICML 2025Progressive Tempering Sampler with Diffusion
- ICML 2025Provable Efficiency of Guidance in Diffusion Models for General Data Distribution
- ICML 2025Provable Maximum Entropy Manifold Exploration via Diffusion Models
- ICML 2025Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers
- ICML 2025Random Policy Evaluation Uncovers Policies of Generative Flow Networks
- ICML 2025ReFrame: Layer Caching for Accelerated Inference in Real-Time Rendering
- ICML 2025REG: Rectified Gradient Guidance for Conditional Diffusion Models
- ICML 2025ReQFlow: Rectified Quaternion Flow for Efficient and High-Quality Protein Backbone Generation
- ICML 2025RestoreGrad: Signal Restoration Using Conditional Denoising Diffusion Models with Jointly Learned Prior
- ICML 2025Rethinking Score Distilling Sampling for 3D Editing and Generation
- ICML 2025Retrieval Augmented Zero-Shot Enzyme Generation for Specified Substrate
- ICML 2025Revisiting Diffusion Models: From Generative Pre-training to One-Step Generation
- ICML 2025Reward-Guided Iterative Refinement in Diffusion Models at Test-Time with Applications to Protein and DNA Design
- ICML 2025Riemannian Diffusion Adaptation for Distributed Optimization on Manifolds
- ICML 2025RIFLEx: A Free Lunch for Length Extrapolation in Video Diffusion Transformers
- ICML 2025RobustLight: Improving Robustness via Diffusion Reinforcement Learning for Traffic Signal Control
- ICML 2025Roll the dice & look before you leap: Going beyond the creative limits of next-token prediction
- ICML 2025S4S: Solving for a Fast Diffusion Model Solver
- ICML 2025SADA: Stability-guided Adaptive Diffusion Acceleration
- ICML 2025SAeUron: Interpretable Concept Unlearning in Diffusion Models with Sparse Autoencoders
- ICML 2025SAH-Drive: A Scenario-Aware Hybrid Planner for Closed-Loop Vehicle Trajectory Generation
- ICML 2025Sample-specific Noise Injection for Diffusion-based Adversarial Purification
- ICML 2025SANA 1.5: Efficient Scaling of Training-Time and Inference-Time Compute in Linear Diffusion Transformer
- ICML 2025SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion
- ICML 2025Scalable Generation of Spatial Transcriptomics from Histology Images via Whole-Slide Flow Matching
- ICML 2025Scalable Non-Equivariant 3D Molecule Generation via Rotational Alignment
- ICML 2025Score as Action: Fine Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning
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