| | --- |
| | library_name: transformers |
| | license: mit |
| | datasets: |
| | - CodeGoat24/UniGenBench-Eval-Images |
| | base_model: |
| | - CodeGoat24/UnifiedReward-2.0-qwen-72b |
| | --- |
| | |
| |
|
| | # UniGenBench-EvalModel-qwen-72b-v1 |
| |
|
| | This model is tailored for offline T2I model evaluation on [UniGenBench](https://github.com/CodeGoat24/UniGenBench), which achieves an average accuracy of 94% compared to evaluations by Gemini 2.5 Pro. |
| |
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| | Feel free to use this model to assess and compare the performance of your models. |
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| | 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](https://codegoat24.github.io) |
| | |
| | |
| | ## Citation |
| | |
| | ```bibtex |
| | @article{UniGenBench++, |
| | title={UniGenBench++: A Unified Semantic Evaluation Benchmark for Text-to-Image Generation}, |
| | author={Wang, Yibin and Li, Zhimin and Zang, Yuhang and Bu, Jiazi and Zhou, Yujie and Xin, Yi and He, Junjun and Wang, Chunyu and Lu, Qinglin and Jin, Cheng and others}, |
| | journal={arXiv preprint arXiv:2510.18701}, |
| | year={2025} |
| | } |
| | |
| | @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} |
| | } |
| | ``` |
