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from dataclasses import dataclass
from enum import Enum
@dataclass
class Task:
benchmark: str
metric: str
col_name: str
# Select your tasks here
# ---------------------------------------------------
class Tasks(Enum):
# task_key in the json file, metric_key in the json file, name to display in the leaderboard
# For MMLongBench-Doc (https://arxiv.org/abs/2407.01523), we use ACC as the main metric
task0 = Task("mmlongbench_doc", "acc", "ACC")
NUM_FEWSHOT = 0 # Change with your few shot
# ---------------------------------------------------
# Your leaderboard name
TITLE = """<h1 align="center" id="space-title">🥇 <a href="https://github.com/CodeGoat24/UniGenBench" target="_blank">UniGenBench</a> Leaderboard (English Long)</h1> """
# Links and conference info
LINKS_AND_INFO = """
<div align="center">
<p><a href="https://hunyuan.tencent.com/" target="_blank">Hunyuan</a>, Tencent</p> <br>
<a href="https://codegoat24.github.io/UnifiedReward/Pref-GRPO" target="_blank">🏠 Homepage</a> |
<a href="https://arxiv.org/pdf/2508.20751" target="_blank">📄 arXiv Paper</a> |
<a href="https://huggingface.co/datasets/CodeGoat24/UniGenBench/tree/main">😊 Huggingface</a>
<a href="https://github.com/CodeGoat24/UniGenBench" target="_blank" rel="noopener noreferrer"><img alt="Code" src="https://img.shields.io/github/stars/CodeGoat24/UniGenBench.svg?style=social&label=Official"></a>
🏅 <a href="https://huggingface.co/spaces/CodeGoat24/UniGenBench_Leaderboard"><b>Leaderboard</b>(English)</a> |
<a href="https://huggingface.co/spaces/CodeGoat24/UniGenBench_Leaderboard_Chinese"><b>Leaderboard</b>(Chinese)</a> |
<a href="https://huggingface.co/spaces/CodeGoat24/UniGenBench_Leaderboard_English_Long"><b>Leaderboard</b>(English Long)</a> |
<a href="https://huggingface.co/spaces/CodeGoat24/UniGenBench_Leaderboard_Chinese_Long"><b>Leaderboard</b>(Chinese Long)</a> 🏅
</div>
"""
# What does your leaderboard evaluate?
INTRODUCTION_TEXT = """
📚 [UniGenBench](https://github.com/CodeGoat24/UniGenBench) is a unified benchmark for T2I generation that integrates diverse prompt themes with a comprehensive suite of fine-grained evaluation criteria.
🔧 You can use the official [GitHub repo](https://github.com/CodeGoat24/UniGenBench) to evaluate your model on [UniGenBench](https://github.com/CodeGoat24/UniGenBench).
😊 We release **all generated images from the T2I models** evaluated in our UniGenBench on [UniGenBench-Eval-Images](https://huggingface.co/datasets/CodeGoat24/UniGenBench-Eval-Images). Feel free to use any evaluation model that is convenient and suitable for you to assess and compare the performance of your models.
📝 To add your own model to the leaderboard, please send an Email to [Yibin Wang](https://codegoat24.github.io/), then we will help with the evaluation and updating the leaderboard.
"""
CITATION_BUTTON_LABEL = "Copy the following snippet to cite these results"
CITATION_BUTTON_TEXT = r"""
@article{UniGenBench&Pref-GRPO,
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}
}
"""
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