# Input Perturbation Reduces Exposure Bias in Diffusion Models

Mang Ning, Enver Sangineto, Angelo Porrello, Simone Calderara, Rita Cucchiara. ICML 2023 (2023).

Studies accumulated sampling errors in diffusion models and trains with perturbed inputs to simulate inference-time prediction errors.

Addresses the same training–sampling mismatch through input perturbation, providing a comparison with scheduled sampling on model-generated states.

[Original paper](https://proceedings.mlr.press/v202/ning23a.html)

## Citation

```bibtex
@inproceedings{pmlr-v202-ning23a,
  title = {{Input Perturbation Reduces Exposure Bias in Diffusion Models}},
  author = {Ning, Mang and Sangineto, Enver and Porrello, Angelo and Calderara, Simone and Cucchiara, Rita},
  year = {2023},
  booktitle = {ICML 2023},
  url = {https://proceedings.mlr.press/v202/ning23a.html}
}
```