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 2,202 篇，第 7 / 45 页
- NeurIPS 2026How Diffusion Models Memorize
- NeurIPS 2026How well behaved is finite dimensional Diffusion Maps embedding?
- NeurIPS 2026Hydra-DP3: Frequency-Aware Right-Sizing of 3D Diffusion Policies for Visuomotor Control
- NeurIPS 2026HyFAD: Hybrid Time-Frequency Diffusion with Frequency-Aware Embedding for Time Series Imputation
- NeurIPS 2026Hypergraph Generation via Structured Stochastic Diffusion
- NeurIPS 2026Hypergraph Generation with Latent Diffusion
- NeurIPS 2026HyperSkill: Multi-Modal Skill Learning on the Unit Hypersphere
- NeurIPS 2026I2V-DETACH: Source Grounding Detachment for Unauthorized Image-to-Video Generation
- NeurIPS 2026IdealCache: Rethinking Cache Scheduling in Diffusion Transformers via Ideal Trajectories
- NeurIPS 2026Improving Diffusion Posterior Samplers with Lagged Temporal Corrections for Image Restoration
- NeurIPS 2026Improving Function Space Flow Matching with Kernel Optimal Transport
- NeurIPS 2026In-Context Learning for Remote Sensing Vision: A Semantic-Aware Rotation-Robust Diffusion Framework
- NeurIPS 2026Inference-Time Refinement Closes the Synthetic-Real Gap in Tabular Diffusion
- NeurIPS 2026Inference-Time Self-Aligned Drifting for Few-Step Flow Matching
- NeurIPS 2026Inferring how internal brain state shapes neural responses with state-dependent diffusion models
- NeurIPS 2026JaSpec-LID: Local Intrinsic Dimension Estimation via Jacobian Spectra of ODE-based Generative Models
- NeurIPS 2026Joint EM Image Super-Resolution and Segmentation with Semantic and Structural Priors
- NeurIPS 2026Keep It CALM: Analyzing the Limits of Global Unsafety in Text-to-Image Generation
- NeurIPS 2026Kernel-Gradient Drifting Models
- NeurIPS 2026Kinetic-Optimal Scheduling with Moment Correction for Metric-Induced Discrete Flow Matching in Zero-Shot Text-to-Speech
- NeurIPS 2026Koopman Generative Operators for Efficient Probabilistic Time-Series Forecasting
- NeurIPS 2026L-Flow: Longitudinal Flow Matching for Progression-Aware Speech Biomarker Modeling
- NeurIPS 2026L2P: Unlocking Latent Potential for Pixel Generation
- NeurIPS 2026LAFP: Preserving Latent Action Structure in Latent Policy Learning via Flow Matching
- NeurIPS 2026LangFlow: Continuous Diffusion Rivals Discrete in Language Modeling
- NeurIPS 2026Laplacian Heads Improve Transformers by Smoothing Token Representations
- NeurIPS 2026Latent Generative Solvers for Generalizable Long-Term Physics Simulation
- NeurIPS 2026Latent Motion Alignment for Video Diffusion
- NeurIPS 2026Latent Process Generator Matching
- NeurIPS 2026Latent Refinement Decoding: Enhancing Diffusion Language Models by Refining Belief States
- NeurIPS 2026Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models
- NeurIPS 2026Layout Before Pixels: Topology-Anchored Transcriptome-to-Histology Generation
- NeurIPS 2026LCD$^3$: Layout-Conditioned Diffusion for Dataset Distillation in Object Detection
- NeurIPS 2026Learn from Your Mistakes: Self-Correcting Masked Diffusion Models
- NeurIPS 2026Learn from your own latents and not from tokens: A sample-complexity theory
- NeurIPS 2026Learning a Maximum Entropy Model for Visual Textures using Diffusion
- NeurIPS 2026Learning Cultural Vectors for Cross-Cultural Generation
- NeurIPS 2026Learning Domain Trajectories with Flow Matching for Gradual Domain Adaptation
- NeurIPS 2026Learning Energy-Based Models from Stochastic Interpolants using Spatiotemporal Differences
- NeurIPS 2026Learning Generative Dynamics for 3D Molecule Generation via Sequential Neuro-Symbolic Constraints
- NeurIPS 2026Learning Hierarchical Forward Processes For Discrete Diffusion Language Models
- NeurIPS 2026Learning Motion-Appearance Coupling Priors for Solving Video Inverse Problems
- NeurIPS 2026Learning Reach-Set Geometry for Tighter Probabilistic Neural Network Verification
- NeurIPS 2026Learning to Solve Generative ODEs Beyond the Linear Span
- NeurIPS 2026Learning Unbiased Permutations via Flow Matching
- NeurIPS 2026Learning Visual Feature-Based World Models via Residual Latent Action
- NeurIPS 2026Learning When to Denoise: Optimizing Asynchronous Schedules for Latent Diffusion
- NeurIPS 2026LENS: Low-Frequency Eigen Noise Shaping for Efficient Diffusion Sampling
- NeurIPS 2026Less Supervision, Better Generalization: Weakly Supervised Fake Region Localization in Diffusion-Edited Images
- NeurIPS 2026Limits and Potential of Score-Based Data Valuation: Redundancy, Complementarity, and Non-Monotonicity
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