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Add paper and GitHub links, update license and citation

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Hi! I'm Niels from the Hugging Face community science team. I've updated the dataset card for Gen-Arena to include:
- Links to the [SCOPE paper](https://huggingface.co/papers/2605.08043), official GitHub repository, and project page.
- Updated the license to MIT (matching the source repository).
- Added the BibTeX citation information.

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  1. README.md +15 -4
README.md CHANGED
@@ -1,12 +1,12 @@
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  ---
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- license: other
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  language:
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  - en
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- pretty_name: Gen-Arena
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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
@@ -17,9 +17,11 @@ tags:
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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 *SCOPE: Structured Decomposition and Conditional Skill Orchestration for Complex Image Generation* 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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@@ -77,4 +79,13 @@ Reference images can be loaded by joining each `reference_image_paths` value wit
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  ## Citation
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- Citation information will be added after the associated paper is publicly available.
 
 
 
 
 
 
 
 
 
 
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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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+
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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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+ ```