metadata
license: cc
datasets:
- QWW/Syncd_filtered
base_model:
- black-forest-labs/FLUX.1-Kontext-dev
pipeline_tag: image-text-to-image
Model Card for Model ID
This is the pre-trained model weight for paper DivRL: Disentangled Self-Similarity Rewards for Diverse Subject-Driven Generation.
- Finetuned from model: FLUX.1-Kontext-dev
- Repository: https://github.com/QianWangX/DivRL
- Paper: https://arxiv.org/abs/2606.23950
- Demo: https://qianwangx.github.io/DivRL/
Uses
Stage-1 weight is trained with nSSM as reward model only. Built on top of Stage-1 weight, Stage-2 weight is further trained on nSSM + VSM collaboratively to obtain the final results shown in the paper.
You can refer to the Stage-1 weight for generation with high diversity but low consistency, and the Stage-2 weight for generation with both high diversity and high consistency.
How to Get Started with the Model
Please refer to https://github.com/QianWangX/DivRL.
Training Details
Training Data
We provide the training data at QWW/Syncd_filtered.
BibTeX:
@misc{wang2026divrl,
title={DivRL: Disentangled Self-Similarity Rewards for Diverse Subject-Driven Generation},
author={Qian Wang and Zhenyu Li and Abdelrahman Eldesokey and Peter Wonka},
year={2026},
eprint={2606.23950},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2606.23950},
}