UniGenBench-EvalModel-qwen-72b-v1

This model is tailored for offline T2I model evaluation on UniGenBench, which achieves an average accuracy of 94% compared to evaluations by Gemini 2.5 Pro.

Feel free to use this model to assess and compare the performance of your models.

For further details, please refer to the following resources:

• 📰 Paper: https://arxiv.org/pdf/2508.20751
• 🪐 Project Page: https://codegoat24.github.io/UnifiedReward/Pref-GRPO
• 🤗 UniGenBench: https://github.com/CodeGoat24/UniGenBench
• 🤗 Leaderboard: https://huggingface.co/spaces/CodeGoat24/UniGenBench_Leaderboard
• 👋 Point of Contact: Yibin Wang

Citation

@article{UniGenBench,
  title={Pref-GRPO: Pairwise Preference Reward-based GRPO for Stable Text-to-Image Reinforcement Learning},
  author={Wang, Yibin and Li, Zhimin and Zang, Yuhang and Zhou, Yujie and Bu, Jiazi and Wang, Chunyu and Lu, Qinglin, and Jin, Cheng and Wang, Jiaqi},
  journal={arXiv preprint arXiv:2508.20751},
  year={2025}
}