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---
license: apache-2.0
pipeline_tag: image-text-to-text
---
# HermesFlow
Official Repository of the paper: *[HermesFlow](https://github.com/Gen-Verse/HermesFlow)*.
<p align="left">
<a href='https://arxiv.org/abs/2502.12148'>
<img src='https://img.shields.io/badge/Arxiv-2502.12148-A42C25?style=flat&logo=arXiv&logoColor=A42C25'></a>
<a href='https://github.com/Gen-Verse/HermesFlow'>
<img src='https://img.shields.io/badge/GitHub-Code-black?style=flat&logo=github&logoColor=white'></a>
</p>
<img src="./pipeline.png" style="zoom:100%;" />
<img src="./image.png" style="zoom:100%;" />
<img src="./image-1.png" style="zoom:100%;" />
## News🔥🔥🔥
* Feb.18, 2025. Our checkpoints are publicly available on [HuggingFace Repo](https://huggingface.co/Gen-Verse/HermesFlow).
## Introduction
HermesFlow is a general alignment framework for multimodal LLMs, which cruate homologous preference data itself and utilize self-play iterative optimization with Pair-DPO to seamlessly close the gap between multimodal understanding and generation.
## Citation
```
@article{yang2025hermesflow,
title={HermesFlow: Seamlessly Closing the Gap in Multimodal Understanding and Generation},
author={Yang, Ling and Zhang, Xinchen and Tian, Ye and Shang, Chenming and Xu, Minghao and Zhang, Wentao and Cui, Bin},
journal={arXiv preprint arXiv:2502.12148},
year={2025}
}
``` |