mlsanityData to 7 Oct 2026

Adversarial score matching and improved sampling for image generation

arXiv 2009.05475 ↗First posted 11 Sep 2020cs.LG cs.CV stat.MLcited by 95

Not on the map. Why?

Cited by 74 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Denoising Score Matching with Annealed Langevin Sampling (DSM-ALS) has recently found success in generative modeling. The approach works by first training a neural network to estimate the score of a distribution, and then using Langevin dynamics to sample from the data distribution assumed by the score network. Despite the convincing visual quality of samples, this method appears to perform worse than Generative Adversarial Networks (GANs) under the Fr'echet Inception Distance, a standard metric for generative models. We show that this apparent gap vanishes when denoising the final Langevin samples using the score network. In addition, we propose two improvements to DSM-ALS: 1) Consistent Annealed Sampling as a more stable alternative to Annealed Langevin Sampling, and 2) a hybrid training formulation, composed of both Denoising Score Matching and adversarial objectives. By combining these two techniques and exploring different network architectures, we elevate score matching methods and obtain results competitive with state-of-the-art image generation on CIFAR-10.

Key facts. Cited by 95 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 Sep 2020.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2020: 2; 2021: 20; 2022: 25; 2023: 24; 2024: 17; 2025: 6; 2026: 1.

95 papers.

Sort:

By area:

  1. 2020Denoising Diffusion Implicit Modelscited by 9,655
  2. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  3. 2021Improved Denoising Diffusion Probabilistic Modelscited by 3,736
  4. 2021SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equationscited by 1,903
  5. 2021Cascaded Diffusion Models for High Fidelity Image Generationcited by 1,155
  6. 2022Diffusion Models: A Comprehensive Survey of Methods and Applicationscited by 1,107
  7. 2022Diffusion Models in Vision: A Surveycited by 1,008
  8. 2023Adversarial Diffusion Distillationcited by 741
  9. 2021DiffusionCLIP: Text-Guided Diffusion Models for Robust Image Manipulationcited by 640
  10. 2021Score-based Generative Modeling in Latent Spacecited by 634
  11. 2021Diffusion Schr"odinger Bridge with Applications to Score-Based Generative Modelingcited by 594
  12. 2021Tackling the Generative Learning Trilemma with Denoising Diffusion GANscited by 515
38 more
  1. 2023Open-Vocabulary Panoptic Segmentation with Text-to-Image Diffusion Modelscited by 371
  2. 2022MCVD: Masked Conditional Video Diffusion for Prediction, Generation, and Interpolationcited by 307
  3. 2022Cold Diffusion: Inverting Arbitrary Image Transforms Without Noisecited by 275
  4. 2022Convergence of denoising diffusion models under the manifold hypothesiscited by 237
  5. 2021Score-Based Generative Modeling with Critically-Damped Langevin Diffusioncited by 230
  6. 2021Gotta Go Fast When Generating Data with Score-Based Modelscited by 218
  7. 2022Riemannian Score-Based Generative Modellingcited by 216
  8. 2022GENIE: Higher-Order Denoising Diffusion Solverscited by 127
  9. 2023State of the Art on Diffusion Models for Visual Computingcited by 126
  10. 2022Score-Based Generative Models Detect Manifoldscited by 121
  11. 2023Diffusion Models for Image Restoration and Enhancement: A Comprehensive Surveycited by 108
  12. 2022Refining Generative Process with Discriminator Guidance in Score-based Diffusion Modelscited by 98
  13. 2023Towards Faster Non-Asymptotic Convergence for Diffusion-Based Generative Modelscited by 84
  14. 2023Reflected Diffusion Modelscited by 81
  15. 2021Diffusion Normalizing Flowcited by 77
  16. 2022Universal Speech Enhancement with Score-based Diffusioncited by 75
  17. 2023Generate What You Prefer: Reshaping Sequential Recommendation via Guided Diffusioncited by 72
  18. 2024A Sharp Convergence Theory for The Probability Flow ODEs of Diffusion Modelscited by 64
  19. 2021Score-based Generative Neural Networks for Large-Scale Optimal Transportcited by 59
  20. 2022SinFusion: Training Diffusion Models on a Single Image or Videocited by 58
  21. 2021Diffusion-Based Representation Learningcited by 57
  22. 2021Adversarial Text-to-Image Synthesis: A Reviewcited by 52
  23. 2021Multimodal Image Synthesis and Editing: The Generative AI Eracited by 52
  24. 2021NU-Wave: A Diffusion Probabilistic Model for Neural Audio Upsamplingcited by 50
  25. 2023Class-Balancing Diffusion Modelscited by 47
  26. 2022Truncated Diffusion Probabilistic Models and Diffusion-based Adversarial Auto-Encoderscited by 42
  27. 2022Maximum Likelihood Training of Implicit Nonlinear Diffusion Modelscited by 42
  28. 2022Diffusion-based Generative Speech Source Separationcited by 41
  29. 2025An Introduction to Flow Matching and Diffusion Modelscited by 33
  30. 2022Full-band General Audio Synthesis with Score-based Diffusioncited by 32
  31. 2022DATID-3D: Diversity-Preserved Domain Adaptation Using Text-to-Image Diffusion for 3D Generative Modelcited by 32
  32. 2022Draw Your Art Dream: Diverse Digital Art Synthesis with Multimodal Guided Diffusioncited by 30
  33. 2023DisDiff: Unsupervised Disentanglement of Diffusion Probabilistic Modelscited by 30
  34. 2022SOS: Score-based Oversampling for Tabular Datacited by 29
  35. 2020Diffusion models for Handwriting Generationcited by 25
  36. 2023Region-Aware Diffusion for Zero-shot Text-driven Image Editingcited by 25
  37. 2023Unifying GANs and Score-Based Diffusion as Generative Particle Modelscited by 21
  38. 2024Deep Generative Models for Offline Policy Learning: Tutorial, Survey, and Perspectives on Future Directionscited by 20

50 most cited of 95 All 95 (JSON)