Datasets:
Add paper and GitHub links, update license and citation
#2
by nielsr HF Staff - opened
README.md
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---
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license: other
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language:
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- en
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-
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size_categories:
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- n<1K
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task_categories:
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- text-to-image
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tags:
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- text-to-image
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- image-generation
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# Gen-Arena
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Gen-Arena is a text-to-image evaluation benchmark for compositional prompt following and reference-conditioned generation. Each sample contains a natural-language generation prompt, optional reference images, named entities, and fine-grained constraints.
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Gen-Arena is introduced in the paper
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This package contains 300 samples across 6 categories:
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## Citation
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---
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language:
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- en
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license: mit
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size_categories:
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- n<1K
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task_categories:
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- text-to-image
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pretty_name: Gen-Arena
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tags:
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- text-to-image
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- image-generation
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# Gen-Arena
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[**Project Page**](https://nopnor.github.io/SCOPE/) | [**Paper**](https://huggingface.co/papers/2605.08043) | [**Code**](https://github.com/nopnor/SCOPE)
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Gen-Arena is a text-to-image evaluation benchmark for compositional prompt following and reference-conditioned generation. Each sample contains a natural-language generation prompt, optional reference images, named entities, and fine-grained constraints.
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Gen-Arena is introduced in the paper [SCOPE: Structured Decomposition and Conditional Skill Orchestration for Complex Image Generation](https://huggingface.co/papers/2605.08043) as a human-annotated benchmark with entity- and constraint-level specifications.
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This package contains 300 samples across 6 categories:
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## Citation
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```bibtex
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@misc{ren2026scope,
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title = {SCOPE: Structured Decomposition and Conditional Skill Orchestration for Complex Image Generation},
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author = {Tianfei Ren and Zhipeng Yan and Yiming Zhao and Zhen Fang and Yu Zeng and Guohui Zhang and Hang Xu and Xiaoxiao Ma and Shiting Huang and Ke Xu and Wenxuan Huang and Lionel Z. Wang and Lin Chen and Zehui Chen and Jie Huang and Feng Zhao},
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year = {2026},
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eprint = {2605.08043},
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archivePrefix = {arXiv},
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url = {https://arxiv.org/abs/2605.08043}
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}
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```
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