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 694 篇，第 9 / 14 页
- NeurIPS 2025Normalized Attention Guidance: Universal Negative Guidance for Diffusion Models
- NeurIPS 2025Normalizing Flows are Capable Models for Continuous Control
- NeurIPS 2025Novel View Synthesis from A Few Glimpses via Test-Time Natural Video Completion
- NeurIPS 2025NPN: Non-Linear Projections of the Null-Space for Imaging Inverse Problems
- NeurIPS 2025NUTS: Eddy-Robust Reconstruction of Surface Ocean Nutrients via Two-Scale Modeling
- NeurIPS 2025ObCLIP: Oblivious CLoud-Device Hybrid Image Generation with Privacy Preservation
- NeurIPS 2025OCTDiff: Bridged Diffusion Model for Portable OCT Super-Resolution and Enhancement
- NeurIPS 2025OmniCast: A Masked Latent Diffusion Model for Weather Forecasting Across Time Scales
- NeurIPS 2025OmniConsistency: Learning Style-Agnostic Consistency from Paired Stylization Data
- NeurIPS 2025Omnidirectional 3D Scene Reconstruction from Single Image
- NeurIPS 2025OmniSync: Towards Universal Lip Synchronization via Diffusion Transformers
- NeurIPS 2025OmniTry: Virtual Try-On Anything without Masks
- NeurIPS 2025OmniVCus: Feedforward Subject-driven Video Customization with Multimodal Control Conditions
- NeurIPS 2025On Efficiency-Effectiveness Trade-off of Diffusion-based Recommenders
- NeurIPS 2025On Inductive Biases That Enable Generalization in Diffusion Transformers
- NeurIPS 2025On scalable and efficient training of diffusion samplers
- NeurIPS 2025On the Closed-Form of Flow Matching: Generalization Does Not Arise from Target Stochasticity
- NeurIPS 2025On the Edge of Memorization in Diffusion Models
- NeurIPS 2025On the Relation between Rectified Flows and Optimal Transport
- NeurIPS 2025One Stone with Two Birds: A Null-Text-Null Frequency-Aware Diffusion Models for Text-Guided Image Inpainting
- NeurIPS 2025One-Step Diffusion for Detail-Rich and Temporally Consistent Video Super-Resolution
- NeurIPS 2025One-Step Diffusion-Based Image Compression with Semantic Distillation
- NeurIPS 2025One-Step is Enough: Sparse Autoencoders for Text-to-Image Diffusion Models
- NeurIPS 2025One-Step Offline Distillation of Diffusion-based Models via Koopman Modeling
- NeurIPS 2025Online Feedback Efficient Active Target Discovery in Partially Observable Environments
- NeurIPS 2025OpenHOI: Open-World Hand-Object Interaction Synthesis with Multimodal Large Language Model
- NeurIPS 2025Optimize Any Topology: A Foundation Model for Shape- and Resolution-Free Structural Topology Optimization
- NeurIPS 2025OSCAR: One-Step Diffusion Codec Across Multiple Bit-rates
- NeurIPS 2025Overcoming Challenges of Long-Horizon Prediction in Driving World Models
- NeurIPS 2025OverLayBench: A Benchmark for Layout-to-Image Generation with Dense Overlaps
- NeurIPS 2025PairEdit: Learning Semantic Variations for Exemplar-based Image Editing
- NeurIPS 2025Pairwise Optimal Transports for Training All-to-All Flow-Based Condition Transfer Model
- NeurIPS 2025PanoWan: Lifting Diffusion Video Generation Models to 360$^\circ$ with Latitude/Longitude-aware Mechanisms
- NeurIPS 2025Pareto-Optimal Energy Alignment for Designing Nature-Like Antibodies
- NeurIPS 2025PAROAttention: Pattern-Aware ReOrdering for Efficient Sparse and Quantized Attention in Visual Generation Models
- NeurIPS 2025PartCrafter: Structured 3D Mesh Generation via Compositional Latent Diffusion Transformers
- NeurIPS 2025Partial Physics Informed Diffusion Model for Ocean Chlorophyll Concentration Reconstruction
- NeurIPS 2025Path Gradients after Flow Matching
- NeurIPS 2025Personalized Image Editing in Text-to-Image Diffusion Models via Collaborative Direct Preference Optimization
- NeurIPS 2025Personalized Visual Content Generation in Conversational Systems
- NeurIPS 2025Perturb a Model, Not an Image: Towards Robust Privacy Protection via Anti-Personalized Diffusion Models
- NeurIPS 2025PhysCtrl: Generative Physics for Controllable and Physics-Grounded Video Generation
- NeurIPS 2025PhysDiff-VTON: Cross-Domain Physics Modeling and Trajectory Optimization for Virtual Try-On
- NeurIPS 2025PhysDiff: A Physically-Guided Diffusion Model for Multivariate Time Series Anomaly Detection
- NeurIPS 2025Physics-Constrained Flow Matching: Sampling Generative Models with Hard Constraints
- NeurIPS 2025Physics-Driven Spatiotemporal Modeling for AI-Generated Video Detection
- NeurIPS 2025Pin the Tail on the Model: Blindfolded Repair of User-Flagged Failures in Text-to-Image Services
- NeurIPS 2025PipeFusion: Patch-level Pipeline Parallelism for Diffusion Transformers Inference
- NeurIPS 2025Pixel-Perfect Depth with Semantics-Prompted Diffusion Transformers
- NeurIPS 2025PixPerfect: Seamless Latent Diffusion Local Editing with Discriminative Pixel-Space Refinement
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