---
license: other
license_name: research-and-educational-use-license
license_link: https://github.com/SNU-VGILab/improvedSelfDistillation/blob/main/LICENSE
---

# improved Self-Distillation

Pretrained weights and evaluation assets for
[Stabilizing Consistency Training: A Flow Map Analysis and Self-Distillation](https://arxiv.org/abs/2601.22679).

Code and instructions are available in the
[GitHub repository](https://github.com/SNU-VGILab/improvedSelfDistillation).

## Contents

- `outputs/`: pretrained checkpoints
- `buffers/vaes/`: VAE checkpoints and latent statistics
- `buffers/refs/`: reference files for FID evaluation

| Checkpoint | Network | Steps | FID50K |
| --- | --- | --- | --- |
| `2026.02.15KST14.22.08-base4` | FlowMapTiT-B/4 (SD-VAE, TrigFlow) | 400K | 14.58 |
| `2026.01.18KST19.26.11-xlarge1` | ADiT-XL/1 (VA-VAE, Linear) | 600K | 2.30 |

## Usage

Place the downloaded `outputs` and `buffers` directories at the top level of
the code repository, then run the provided training or evaluation scripts.

```bash
bash eval.sh
```

## Citation

```bibtex
@misc{kim2026stabilizingconsistencytrainingflow,
      title={Stabilizing Consistency Training: A Flow Map Analysis and Self-Distillation},
      author={Youngjoong Kim and Duhoe Kim and Woosung Kim and Jaesik Park},
      year={2026},
      eprint={2601.22679},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2601.22679},
}
```