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 6,899 篇，第 121 / 138 页
- NeurIPS 2024InterControl: Zero-shot Human Interaction Generation by Controlling Every Joint
- NeurIPS 2024InterDreamer: Zero-Shot Text to 3D Dynamic Human-Object Interaction
- NeurIPS 2024Interpreting the Weight Space of Customized Diffusion Models
- NeurIPS 2024Invertible Consistency Distillation for Text-Guided Image Editing in Around 7 Steps
- NeurIPS 2024Invisible Image Watermarks Are Provably Removable Using Generative AI
- NeurIPS 2024IR-CM: The Fast and General-purpose Image Restoration Method Based on Consistency Model
- NeurIPS 2024Is One GPU Enough? Pushing Image Generation at Higher-Resolutions with Foundation Models.
- NeurIPS 2024Kaleido Diffusion: Improving Conditional Diffusion Models with Autoregressive Latent Modeling
- NeurIPS 2024KOALA: Empirical Lessons Toward Memory-Efficient and Fast Diffusion Models for Text-to-Image Synthesis
- NeurIPS 2024LaSe-E2V: Towards Language-guided Semantic-aware Event-to-Video Reconstruction
- NeurIPS 2024Latent Diffusion for Neural Spiking Data
- NeurIPS 2024Latent Representation Matters: Human-like Sketches in One-shot Drawing Tasks
- NeurIPS 2024LCGen: Mining in Low-Certainty Generation for View-consistent Text-to-3D
- NeurIPS 2024Learning an Actionable Discrete Diffusion Policy via Large-Scale Actionless Video Pre-Training
- NeurIPS 2024Learning diffusion at lightspeed
- NeurIPS 2024Learning Diffusion Priors from Observations by Expectation Maximization
- NeurIPS 2024Learning Discrete Concepts in Latent Hierarchical Models
- NeurIPS 2024Learning Distributions on Manifolds with Free-Form Flows
- NeurIPS 2024Learning Image Priors Through Patch-Based Diffusion Models for Solving Inverse Problems
- NeurIPS 2024Learning Multimodal Behaviors from Scratch with Diffusion Policy Gradient
- NeurIPS 2024Learning Superconductivity from Ordered and Disordered Material Structures
- NeurIPS 2024Learning the Infinitesimal Generator of Stochastic Diffusion Processes
- NeurIPS 2024Learning-to-Cache: Accelerating Diffusion Transformer via Layer Caching
- NeurIPS 2024Leveraging an ECG Beat Diffusion Model for Morphological Reconstruction from Indirect Signals
- NeurIPS 2024Leveraging Catastrophic Forgetting to Develop Safe Diffusion Models against Malicious Finetuning
- NeurIPS 2024Leveraging Drift to Improve Sample Complexity of Variance Exploding Diffusion Models
- NeurIPS 2024Lexicon3D: Probing Visual Foundation Models for Complex 3D Scene Understanding
- NeurIPS 2024LiteVAE: Lightweight and Efficient Variational Autoencoders for Latent Diffusion Models
- NeurIPS 2024LLM-based Skill Diffusion for Zero-shot Policy Adaptation
- NeurIPS 2024Local Curvature Smoothing with Stein's Identity for Efficient Score Matching
- NeurIPS 2024Localize, Understand, Collaborate: Semantic-Aware Dragging via Intention Reasoner
- NeurIPS 2024Locating What You Need: Towards Adapting Diffusion Models to OOD Concepts In-the-Wild
- NeurIPS 2024Lorentz-Equivariant Geometric Algebra Transformers for High-Energy Physics
- NeurIPS 2024Lumina-Next : Making Lumina-T2X Stronger and Faster with Next-DiT
- NeurIPS 2024MADiff: Offline Multi-agent Learning with Diffusion Models
- NeurIPS 2024Magnet: We Never Know How Text-to-Image Diffusion Models Work, Until We Learn How Vision-Language Models Function
- NeurIPS 2024Make-An-Agent: A Generalizable Policy Network Generator with Behavior-Prompted Diffusion
- NeurIPS 2024MambaTalk: Efficient Holistic Gesture Synthesis with Selective State Space Models
- NeurIPS 2024Markovian Flow Matching: Accelerating MCMC with Continuous Normalizing Flows
- NeurIPS 2024MaskFactory: Towards High-quality Synthetic Data Generation for Dichotomous Image Segmentation
- NeurIPS 2024Maximum Entropy Inverse Reinforcement Learning of Diffusion Models with Energy-Based Models
- NeurIPS 2024MC-DiT: Contextual Enhancement via Clean-to-Clean Reconstruction for Masked Diffusion Models
- NeurIPS 2024Membership Inference on Text-to-Image Diffusion Models via Conditional Likelihood Discrepancy
- NeurIPS 2024MeshFormer : High-Quality Mesh Generation with 3D-Guided Reconstruction Model
- NeurIPS 2024Meta-Diffu$B$: A Contextualized Sequence-to-Sequence Text Diffusion Model with Meta-Exploration
- NeurIPS 2024Metric Flow Matching for Smooth Interpolations on the Data Manifold
- NeurIPS 2024MIDGArD: Modular Interpretable Diffusion over Graphs for Articulated Designs
- NeurIPS 2024MMM-RS: A Multi-modal, Multi-GSD, Multi-scene Remote Sensing Dataset and Benchmark for Text-to-Image Generation
- NeurIPS 2024Model-based Diffusion for Trajectory Optimization
- NeurIPS 2024MoLE: Enhancing Human-centric Text-to-image Diffusion via Mixture of Low-rank Experts
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