RESEARCH PAPERYear 2023

Consistency Models

Yang Song; Prafulla Dhariwal; Mark Chen; Ilya Sutskever

Classification

Major category: Foundational work
Quadrant: Not applicable
Architecture: Not applicable
Prediction paradigm: Not applicable
Subcategories: Diffusion & flow-matching foundations Training optimization & distillation
Source review status: Verified from primary sources

Category review. Consistency Models supplies a general endpoint parameterization and training/distillation framework for fast generation, evaluated on images. It is pre-2026 generative-method background, not a standalone WAM encoder/backbone just because neural simulators later use consistency decoders. Reading evidence

AT A GLANCE

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BibTeX

@InProceedings{cm,
  title = 	 {Consistency Models},
  author =       {Song, Yang and Dhariwal, Prafulla and Chen, Mark and Sutskever, Ilya},
  booktitle = 	 {ICML},
  pages = 	 {32211--32252},
  year = 	 {2023},
  volume = 	 {202},
  month = 	 {23--29 Jul},
}

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BibTeX

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