@article{ryu2026qdrift,
  title = {Q-Drift: Quantization-Aware Drift Correction for Diffusion Model Sampling},
  author = {Ryu, Sooyoung and Salzmann, Mathieu and Javed, Saqib},
  journal = {arXiv preprint arXiv:2603.18095},
  year = {2026},
  month = mar,
  doi = {10.48550/arXiv.2603.18095},
  arxiv = {2603.18095},
  code = {https://github.com/sooyoung-ryu/Q-Drift},
  website = {https://sooyoung-ryu.github.io/Q-Drift/},
  abstract = {Q-Drift uses an offline-calibrated correction factor to rescale diffusion sampler updates under quantization. The correction keeps quantized weights fixed and requires no retraining or additional model evaluations at inference. Experiments cover six text-to-image models, three samplers, and two post-training quantization methods.},
  bibtex_show = {true},
  selected = {true}
}