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

每年论文数

各会议论文数

按年份和会议统计

扩散模型论文数,按年份和会议
年份NeurIPSICLRICMLCVPR合计
202332786109138660
20245202601954961,471
20256944873465512,078
20266616947286082,691

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

全部扩散模型论文

共 2,202 篇,第 13 / 45 页

  1. NeurIPS 2026Train-free Data Poisoning Attack against Retrieval-augmented Diffusion Models
  2. NeurIPS 2026Trainable Sparse Attention via Hybrid Top-k+Top-p Masking and Distillation Fine-Tuning
  3. NeurIPS 2026Training Optimal Large Diffusion Language Models
  4. NeurIPS 2026Training-Free Generative Sampling via Moment-Matched Score Smoothing
  5. NeurIPS 2026Trajectory as the Teacher: Few-Step Discrete Flow Matching via Energy-Navigated Distillation
  6. NeurIPS 2026Trajectory-Consistent Diffusion Policies for Offline Reinforcement Learning
  7. NeurIPS 2026Transforming Image Editors into Video Editors
  8. NeurIPS 2026Transporting Quantiles to Codebook: Scalable Vector Quantization without Codebook Collapse
  9. NeurIPS 2026Tree-Sliced Orlicz Integral Probability Metric
  10. NeurIPS 2026Tri-Prompting: Controllable Video Generation with Scene, Subject, and Motion Prompts
  11. NeurIPS 2026Trivialized Generative Models on Lie Groups
  12. NeurIPS 2026Trustworthy and Efficient Map-free LiDAR Localization via Scan-Pose Alignment and Flow Matching
  13. NeurIPS 2026TUBE: Tangent Upper Bound on Evidence for Discrete Diffusion Language Models
  14. NeurIPS 2026Tunable Latent Generative Priors for Compressed Sensing and Inverse Problems
  15. NeurIPS 2026Two-Sided Learning in Matching Markets with Interviews
  16. NeurIPS 2026Tyche: One Step Flow for Efficient Probabilistic Weather Forecasting
  17. NeurIPS 2026Ultra Flash: Scaling Real-Time Streaming Video Generation to High Resolutions
  18. NeurIPS 2026Unaligned Image Guided Denoising via Cross-modal Conditional Flow Matching
  19. NeurIPS 2026Uncertainty Quantification for Large Language Diffusion Models
  20. NeurIPS 2026Understanding diffusion models requires rethinking (again) generalization
  21. NeurIPS 2026UniCustom: Unified Visual Conditioning for Multi-reference Image Generation
  22. NeurIPS 2026UniFlowDock: Flexible Docking with Complete Equivariant Velocity Fields
  23. NeurIPS 2026Uniform Diffusion Models revisited: Leave-One-Out Denoiser and Absorbing State Reformulation
  24. NeurIPS 2026Universal Time Series Generation with Neural Controlled Differential Equations
  25. NeurIPS 2026Unlocking the Duality between Flow and Field Matching
  26. NeurIPS 2026Unsupervised Concept Discovery with Dirichlet Concept Diffusion Models
  27. NeurIPS 2026V2VFusion: Text-Controlled Video-to-Video Diffusion for Degradation-Aware Video Fusion
  28. NeurIPS 2026Value-Rectified Distillation for Flow-based Offline Reinforcement Learning
  29. NeurIPS 2026Variable-Length Generative Protein Design via Generalized Poisson Flow
  30. NeurIPS 2026Variance Reduction for Expectations with Diffusion Teachers
  31. NeurIPS 2026Variance-Averse n-Step Offline Reinforcement Learning for Sparse Long-Horizon Environments
  32. NeurIPS 2026Variational Active Flow Matching for Discrete Online Black-Box Optimization
  33. NeurIPS 2026Variational Trajectory Optimization of Anisotropic Diffusion Schedules
  34. NeurIPS 2026Velocity Ambiguity Profiles: Time-Resolved Bayes-Risk Diagnostics for Flow Matching
  35. NeurIPS 2026Vermeer: Autoregressive generative modeling of microscopy predicts protein localization
  36. NeurIPS 2026VGB for Masked Diffusion Model: Efficient Test-time Scaling for Reward Satisfaction and Sample Editing
  37. NeurIPS 2026Video Models Can Reason with Verifiable Rewards
  38. NeurIPS 2026Virtual-Flow: Virtual Microphone-based Speech Enhancement via Unsupervised Flow Matching
  39. NeurIPS 2026Visual-Redundancy-Controlled Parallel Decoding for Diffusion-Based Multimodal Large Language Models
  40. NeurIPS 2026Volatility-Whitened Probabilistic Residual Modeling for Long-Term Time Series Forecasting
  41. NeurIPS 2026VolCo: Volumetric Contact for High-Fidelity Human Grasp Generation
  42. NeurIPS 2026VolFill: Single-View Amodal 3D Scene Reconstruction with Volumetric Flow Matching
  43. NeurIPS 2026Wasserstein Gradient Flows and Forward-Only Diffusion Are Not Enough for Multimodal Sampling
  44. NeurIPS 2026Watermarking as a Learned Intrinsic Property of Diffusion Models
  45. NeurIPS 2026Wavelet Flow Matching for Multi-Scale Physics Emulation
  46. NeurIPS 2026What kills $v$-prediction? A Patch-wise PCA Perspective on Pixel-Space Flow Matching
  47. NeurIPS 2026What Makes a Good Path? Factoring Manifold Support and Path Geometry
  48. NeurIPS 2026What Matters for Diffusion-Friendly Latent Manifold? Prior-Aligned Autoencoders for Latent Diffusion
  49. NeurIPS 2026What Time Is It? How Data Geometry Makes Time Conditioning Optional for Flow Matching
  50. NeurIPS 2026When Edge Independence Fails: Joint Graph Diffusion with Latent Sociability Priors

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"}

两分钟接入 Paperlist MCP(Claude Code、Cursor、Codex、ChatGPT)

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。

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