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TITLE = """<h1 align="center" id="space-title">🔥🏅️GenCeption Leaderboard 🏅️🔥</h1>"""

BANNER = """<div>
<p align="center">
  <a href="https://github.com/EQTPartners/GenCeption/">GitHub</a>&emsp;•&emsp;
  <a href="https://github.com/EQTPartners/GenCeption#contribute">Contribute</a>&emsp;•&emsp;
  <a href="https://arxiv.org/abs/2402.14973">Paper</a>&emsp;•&emsp;
  <a href="https://github.com/EQTPartners/GenCeption#cite-this-work">Citation</a> 
</p>
"""

INTRO = """GenCeption is an annotation-free MLLM (Multimodal Large Language Model) evaluation framework that merely requires unimodal data to assess inter-modality semantic coherence and inversely reflects the models' inclination to hallucinate."""
INTRO2 = """This leaderboard displays the evaluated models ranked by their performance on the **GC@3** metric, as defined in [GenCeption: Evaluate Multimodal LLMs with Unlabeled Unimodal Data](https://arxiv.org/abs/2402.14973). For contributing a model evaluation, please submit a pull request on [GitHub](https://github.com/EQTPartners/GenCeption)."""

CITATION_BUTTON_LABEL = "Copy the following snippet to cite this benchmark"
CITATION_BUTTON_TEXT = r"""
@article{cao2023genception,
    author = {Lele Cao and
              Valentin Buchner and
              Zineb Senane and
              Fangkai Yang},
    title = {{GenCeption}: Evaluate Multimodal LLMs with Unlabeled Unimodal Data},
    year={2023},
    journal={arXiv preprint arXiv:2402.14973},
    primaryClass={cs.AI,cs.CL,cs.LG}
}
"""