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 33 / 42 页
- NeurIPS 2025Fast Monte Carlo Tree Diffusion: 100× Speedup via Parallel and Sparse Planning
- NeurIPS 2025Fast Solvers for Discrete Diffusion Models: Theory and Applications of High-Order Algorithms
- NeurIPS 2025FAST: Foreground‑aware Diffusion with Accelerated Sampling Trajectory for Segmentation‑oriented Anomaly Synthesis
- NeurIPS 2025Faster Video Diffusion with Trainable Sparse Attention
- NeurIPS 2025Federated Dialogue-Semantic Diffusion for Emotion Recognition under Incomplete Modalities
- NeurIPS 2025Feedback Guidance of Diffusion Models
- NeurIPS 2025Finding Low-Rank Matrix Weights in DNNs via Riemannian Optimization: RAdaGrad and RAdamW
- NeurIPS 2025Fine-Tuning Discrete Diffusion Models with Policy Gradient Methods
- NeurIPS 2025FlashMo: Geometric Interpolants and Frequency-Aware Sparsity for Scalable Efficient Motion Generation
- NeurIPS 2025Flatten Graphs as Sequences: Transformers are Scalable Graph Generators
- NeurIPS 2025Flexible MOF Generation with Torsion-Aware Flow Matching
- NeurIPS 2025FlexVAR: Flexible Visual Autoregressive Modeling without Residual Prediction
- NeurIPS 2025FlexWorld: Progressively Expanding 3D Scenes for Flexible-View Exploration
- NeurIPS 2025Flow Density Control: Generative Optimization Beyond Entropy-Regularized Fine-Tuning
- NeurIPS 2025Flow Matching Neural Processes
- NeurIPS 2025Flow Matching-Based Autonomous Driving Planning with Advanced Interactive Behavior Modeling
- NeurIPS 2025Flow-Based Policy for Online Reinforcement Learning
- NeurIPS 2025Flow-GRPO: Training Flow Matching Models via Online RL
- NeurIPS 2025FlowDAS: A Stochastic Interpolant-based Framework for Data Assimilation
- NeurIPS 2025FlowMo: Variance-Based Flow Guidance for Coherent Motion in Video Generation
- NeurIPS 2025FlowNet: Modeling Dynamic Spatio-Temporal Systems via Flow Propagation
- NeurIPS 2025FNOPE: Simulation-based inference on function spaces with Fourier Neural Operators
- NeurIPS 2025ForceFM: Enhancing Protein-Ligand Predictions through Force-Guided Flow Matching
- NeurIPS 2025Forecasting in Offline Reinforcement Learning for Non-stationary Environments
- NeurIPS 2025Fourier Token Merging: Understanding and Capitalizing Frequency Domain for Efficient Image Generation
- NeurIPS 2025FPSAttention: Training-Aware FP8 and Sparsity Co-Design for Fast Video Diffusion
- NeurIPS 2025Fractional Diffusion Bridge Models
- NeurIPS 2025Frame Context Packing and Drift Prevention in Next-Frame-Prediction Video Diffusion Models
- NeurIPS 2025Frame In-N-Out: Unbounded Controllable Image-to-Video Generation
- NeurIPS 2025Free-Lunch Color-Texture Disentanglement for Stylized Image Generation
- NeurIPS 2025FreeControl: Efficient, Training-Free Structural Control via One-Step Attention Extraction
- NeurIPS 2025FreeInv: Free Lunch for Improving DDIM Inversion
- NeurIPS 2025From Cradle to Cane: A Two-Pass Framework for High-Fidelity Lifespan Face Aging
- NeurIPS 2025From Softmax to Score: Transformers Can Effectively Implement In-Context Denoising Steps
- NeurIPS 2025From stability of Langevin diffusion to convergence of proximal MCMC for non-log-concave sampling
- NeurIPS 2025FSI-Edit: Frequency and Stochasticity Injection for Flexible Diffusion-Based Image Editing
- NeurIPS 2025FUDOKI: Discrete Flow-based Unified Understanding and Generation via Kinetic-Optimal Velocities
- NeurIPS 2025Functional Matching of Logic Subgraphs: Beyond Structural Isomorphism
- NeurIPS 2025Fuse2Match: Training-Free Fusion of Flow, Diffusion, and Contrastive Models for Zero-Shot Semantic Matching
- NeurIPS 2025GenColor: Generative and Expressive Color Enhancement with Pixel-Perfect Texture Preservation
- NeurIPS 2025GeneFlow: Translation of Single-cell Gene Expression to Histopathological Images via Rectified Flow
- NeurIPS 2025GeneMAN: Generalizable Single-Image 3D Human Reconstruction from Multi-Source Human Data
- NeurIPS 2025Generating Full-field Evolution of Physical Dynamics from Irregular Sparse Observations
- NeurIPS 2025Generating Informative Samples for Risk-Averse Fine-Tuning of Downstream Tasks
- NeurIPS 2025Generation as Search Operator for Test-Time Scaling of Diffusion-based Combinatorial Optimization
- NeurIPS 2025Generative Data Augmentation via Diffusion Distillation, Adversarial Alignment, and Importance Reweighting
- NeurIPS 2025Generative diffusion for perceptron problems: statistical physics analysis and efficient algorithms
- NeurIPS 2025Generative Distribution Embeddings
- NeurIPS 2025Generative Modeling of Full-Atom Protein Conformations using Latent Diffusion on Graph Embeddings
- NeurIPS 2025Generative Perception of Shape and Material from Differential Motion
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