Diffusion Models papers, 2023–2026
Diffusion, flow matching, and score-based generative modeling
Scope: NeurIPS, ICLR, ICML and CVPR, 2023–2026. 6,900 papers are tagged with this topic.
Key findings
- Diffusion Models went from 660 papers in 2023 to 2,691 in 2026, roughly 4.1x in three years.
- NeurIPS publishes the most Diffusion Models work: 2,202 papers from 2023 to 2026, 32% of the four-venue total.
- The fastest-growing overlap is with Applications · chemistry physics and earth sciences: papers tagged with both rose from 14 in 2023 to 163 in 2026.
- Among the 11 topics under Deep Learning, it ranks #1 by 2026 paper count; the fastest grower in the group, Deep learning · foundation models, is up 2.5x versus 4.1x here.
Papers per venue
Counts by year and venue
| Year | NeurIPS | ICLR | ICML | CVPR | Total |
|---|---|---|---|---|---|
| 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 |
Representative papers
Spread across years and venues so every edition shows up
- 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
All Diffusion Models papers
2,690 papers, page 49 of 54
- NeurIPS 2026Mesh BDF: Barycentric Dominance Field for 3D Native Mesh Generation
- NeurIPS 2026Metric Depth Estimation from Arbitrarily Degraded Low-Resolution Depth Prompts
- NeurIPS 2026Metropolis-Adjusted Diffusion Models
- NeurIPS 2026MFlowAudio: Efficient Text-to-Audio Synthesis via Mamba-based Stateful Flow Matching
- NeurIPS 2026MiCo: Microstructure-Consistent Flow Matching for Diffusion MRI Angular Super-Resolution
- NeurIPS 2026MilliVid: Adaptive Latents for Long-Range Consistency in Video Generation
- NeurIPS 2026MissPath-FM: Flow Matching with Structured Priors for Partially Observed Time Series
- NeurIPS 2026Mitigating Compounding Errors in Online Reinforcement Learning via Optimal Transport Regularized Flow Matching
- NeurIPS 2026Mitigating Over-squashing without Rewiring: A Sheaf Effective Resistance Perspective
- NeurIPS 2026Mix-Opt: Mixed Optimization for Memory-Efficient Personalization of Text-to-Image Diffusion Models
- NeurIPS 2026Mixed-Curvature Geometric Latent Diffusion Model for Graph Generation
- NeurIPS 2026MobileWan: Closing the Quality Gap for Mobile Video Diffusion
- NeurIPS 2026MolHIT: Advancing Molecular-Graph Generation with Hierarchical Discrete Diffusion Models
- NeurIPS 2026MonarchRT: Efficient Attention for Real-Time Video Generation
- NeurIPS 2026MONET: A Massive, Open, Non-redundant and Enriched Text-to-image dataset
- NeurIPS 2026MotionGrounder: Grounded Multi-Object Motion Transfer via Diffusion Transformer
- NeurIPS 2026Move on Muon : A Hamiltonian probability gradient flow perspective of Muon optimizer
- NeurIPS 2026Multilevel and Sequential Monte Carlo for Training-Free Diffusion Guidance
- NeurIPS 2026MUNI: Multimodal Unified Latent Diffusion for Coherent Any-to-Any Generation
- NeurIPS 2026My Video Stays Mine: Temporally Consistent Universal Adversarial Perturbations against Video Customization
- NeurIPS 2026NAGO: Noise-Aware Generative Operator via Flow Matching
- NeurIPS 2026Nahual: A Sequence Model for Language and Atoms
- NeurIPS 2026NDPP-Grasp: Non-Differentiable Physical Plausibility Constraint-Guided Task-Oriented Dexterous Grasp Generation
- NeurIPS 2026NEAT: Neighborhood-Guided, Efficient, Autoregressive Set Transformer for 3D Molecular Generation
- NeurIPS 2026Neural Continuous-Time Markov Chain: Discrete Diffusion via Decoupled Jump Timing and Direction
- NeurIPS 2026Neural Galerkin Normalizing Flows for Bayesian Inference of Diffusions with Inaccessible Boundaries
- NeurIPS 2026Noise-Started One-Step Image Super-Resolution via LR-Conditioned SplitMeanFlow and GAN Refinement
- NeurIPS 2026Normalizing Flows are Capable Trajectory Planners
- NeurIPS 2026Normalizing Trajectory Models
- NeurIPS 2026NSARM: Next-Scale Autoregressive Modeling for Robust Real-World Image Super-Resolution
- NeurIPS 2026ODDR: One-Step Deshadow Diffusion via Reward Guidance
- NeurIPS 2026Offline Inverse Reinforcement Learning with Unified Diffusion Planning
- NeurIPS 2026On Reparameterizing the Score Function
- NeurIPS 2026On the Design Space of Discrete Diffusion Online Adaptation for Molecular Optimization
- NeurIPS 2026On the Limits of Latent Reuse in Diffusion Models
- NeurIPS 2026On the Memorization of Consistency Distillation for Diffusion Models
- NeurIPS 2026Opening the Black Box of Classifier-Free Guidance via Information Bottleneck
- NeurIPS 2026OpenVTON-Bench: A Large-Scale High-Resolution Benchmark for Controllable Virtual Try-On Evaluation
- NeurIPS 2026Optimal Convergence Analysis of DDPM for General Distributions
- NeurIPS 2026ORCA: Hunting Compositional Failures in Text-to-Image Diffusion
- NeurIPS 2026Order-Marginalized Scoring for Masked Diffusion Models
- NeurIPS 2026Order-Optimal Sample Complexity for Distribution Learning via Flow Matching
- NeurIPS 2026Orthrus: Memory-Efficient Parallel Token Generation via Dual-View Diffusion
- NeurIPS 2026Outlier-robust Diffusion Posterior Sampling for Bayesian Inverse Problems
- NeurIPS 2026Oversmoothing as Representation Degeneracy in Neural Sheaf Diffusion
- NeurIPS 2026PACE-dLLM: Elastic Block Decoding via Confidence Cliff Estimation for Diffusion Language Models
- NeurIPS 2026Panoptic Scene Program Diffusion Transformer
- NeurIPS 2026Parallel Rollout Approximation for Pixel-Space Autoregressive Image Generation
- NeurIPS 2026ParaPC-FM: Accelerating Parallel Sampling via Principled Initialization
- NeurIPS 2026Path-Guided Flow Matching for Dataset Distillation
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FAQ
- How many Diffusion Models papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?
- 6,900 in total: 660 in 2023, 1,471 in 2024, 2,078 in 2025, 2,691 in 2026.
- How many Diffusion Models papers are at NeurIPS 2026?
- NeurIPS 2026 has 661 Diffusion Models papers, versus 694 the year before.
- How many Diffusion Models papers are at ICLR 2026?
- ICLR 2026 has 694 Diffusion Models papers, versus 487 the year before.
- How many Diffusion Models papers are at ICML 2026?
- ICML 2026 has 728 Diffusion Models papers, versus 346 the year before.
- How many Diffusion Models papers are at CVPR 2026?
- CVPR 2026 has 608 Diffusion Models papers, versus 551 the year before.
- Which conference publishes the most Diffusion Models papers?
- NeurIPS, with 2,202 papers from 2023 to 2026.
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- Deep learning · probabilistic methods 637
- Deep learning · foundation models 536
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- Deep learning · transfer learning 197