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@@ -390,4 +390,34 @@ license: mit
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  language:
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  - en
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  pretty_name: visual_language
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  language:
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  - en
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  pretty_name: visual_language
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+ ---
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+
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+ # Introduction
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+
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+ This dataset is used to evaluate how Large Vision-Language Models (LVLMs) perform the visual question-answering tasks: understanding the input image or halluciating with the knowledge in the language module.
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+
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+ We provide a testmini set that includes all types of evaluations.
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+
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+ # Citation
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+
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+ If you use this dataset, please cite our paper:
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+
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+ ```
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+ @article{DBLP:journals/corr/abs-2410-00193,
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+ author = {Buse Giledereli and
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+ Yifan Hou and
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+ Yilei Tu and
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+ Mrinmaya Sachan},
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+ title = {Do Vision-Language Models Really Understand Visual Language?},
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+ journal = {CoRR},
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+ volume = {abs/2410.00193},
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+ year = {2024},
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+ url = {https://doi.org/10.48550/arXiv.2410.00193},
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+ doi = {10.48550/ARXIV.2410.00193},
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+ eprinttype = {arXiv},
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+ eprint = {2410.00193},
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+ timestamp = {Tue, 05 Nov 2024 20:39:06 +0100},
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+ biburl = {https://dblp.org/rec/journals/corr/abs-2410-00193.bib},
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+ bibsource = {dblp computer science bibliography, https://dblp.org}
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+ }
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+ ```