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 4 / 28 页
- ICML 2026Dimension-free convergence of diffusion models for approximate Gaussian mixtures
- ICML 2026Dimension-Free Multimodal Sampling via Preconditioned Annealed Langevin Dynamics
- ICML 2026Direct Flow Q-Learning
- ICML 2026DirectEdit: Step-Level Accurate Inversion for Flow-Based Image Editing
- ICML 2026DiscoForcing: A Unified Framework for Real-Time Audio-Driven Character Control with Diffusion Forcing
- ICML 2026DiScoFormer: Plug-In Density and Score Estimation with Transformers
- ICML 2026Discovering Symmetry Groups with Flow Matching
- ICML 2026Discrete Diffusion Samplers and Bridges: Off-Policy Algorithms and Applications in Latent Spaces
- ICML 2026Discrete Diffusion with Physical Mass Constraints for \emph{De Novo} Peptide Sequencing
- ICML 2026Discrete Tilt Matching
- ICML 2026DisPOSE: Projected Polystochastic Diffusion for Self-Supervised Multi-View 3D Human Pose Estimation
- ICML 2026Distillation Models are Good Samplers for Diffusion Reinforcement Learning
- ICML 2026DIVER: Diving Deeper into Distilled Data via Expressive Semantic Recovery
- ICML 2026Divide-and-Denoise: A Game-Theoretic Method for Fairly Composing Diffusion Models
- ICML 2026dLLM-Cache: Accelerating Diffusion Large Language Models with Adaptive Caching
- ICML 2026DLLMQuant: A Post-Training Quantization Framework Tailored for Diffusion-Based Large Language Models
- ICML 2026DLM-Scope: Mechanistic Interpretability of Diffusion Language Models via Sparse Autoencoders
- ICML 2026DSB: Dynamic Sliding Block Scheduling for Diffusion LLMs
- ICML 2026dTRPO : Trajectory Reduction in Policy Optimization of Diffusion Large Language Models
- ICML 2026Dual Optimal Transport for Multi-Concept Composition: Structural Alignment and Texture Injection in Diffusion Models
- ICML 2026Dual-Stream Diffusion for World-Model Augmented Vision-Language-Action Model
- ICML 2026Dual-View Predictive Diffusion: Lightweight Speech Enhancement via Spectrogram-Image Synergy
- ICML 2026DyLLM: Efficient Diffusion LLM Inference via Saliency-based Token Selection and Partial Attention
- ICML 2026DynaMem: Consistent Long Video Generation via Hierarchical Memory and Motion Priors
- ICML 2026Dynamic Compression Flows for Neuroscience Data
- ICML 2026Dynamic Fractal Mamba: A Neural Renormalization Group Flow for Scale-Invariant Sequence Modeling
- ICML 2026DynaTok: Token-Based 4D Reconstruction from Partial Point Clouds
- ICML 2026DyPE: Dynamic Position Extrapolation for Ultra High Resolution Diffusion
- ICML 2026Early Decisions Matter: Proximity Bias and Initial Trajectory Shaping in Non-Autoregressive Diffusion Language Models
- ICML 2026Edit-Based Refinement for Parallel Masked Diffusion Language Models
- ICML 2026Efficient and Uncertainty-Aware Diffusion Framework for Offline-to-Online Reinforcement Learning
- ICML 2026Efficient Diffusion LLMs via Temporal-Spatial Parallel Decoding and Confidence Extrapolation
- ICML 2026Efficient Diffusion Models under Nonconvex Equality and Inequality constraints via Landing
- ICML 2026Efficient Diffusion Models via Time Step Optimization with Consistent Training and Inference Constraints
- ICML 2026Efficient Generative Modeling beyond Memoryless Diffusion via Adjoint Schrödinger Bridge Matching
- ICML 2026Efficient Online Influence Maximization under the Independent Cascade Model with Node-Level Feedback
- ICML 2026Efficient Parallel Samplers for Recurrent-Depth Models and Their Connection to Diffusion Language Models
- ICML 2026Efficient Tail-Aware Generative Optimization via Flow Model Fine-Tuning
- ICML 2026Efficient Test-Time Scaling via Hierarchical Search and Self-Verification for Discrete Diffusion Language Models
- ICML 2026Efficient-DLM: From Autoregressive to Diffusion Language Models, and Beyond in Speed
- ICML 2026Efficient, Property-Aligned Fan-Out Retrieval via RL-Compiled Diffusion
- ICML 2026EgoTactile: Learning Grasp Pressure for Everyday Objects from Egocentric Video
- ICML 2026EigenCache: Rethinking Diffusion Acceleration as Covariance-Optimal Forecasting and Submodular Information Allocation
- ICML 2026Elastic Diffusion Transformer
- ICML 2026Elign: Equivariant Diffusion Model Alignment from Foundational Machine Learned Force Fields
- ICML 2026Embedding-perturbed Exploration Preference Optimization for Flow Models
- ICML 2026Energy-based Compositional Diffusion Planning
- ICML 2026Enhanced Latent-Space Adversarial Training for Super-Resolution
- ICML 2026Enhancing Membership Inference Attacks on Diffusion Models from a Frequency-Domain Perspective
- ICML 2026Enhancing Reasoning for Diffusion LLMs via Distribution Matching Policy Optimization
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