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πŸš€ [NeurIPS24] Make Vision Matter in Visual-Question-Answering (VQA)! Introducing NaturalBench, a vision-centric VQA benchmark (NeurIPS'24) that challenges vision-language models with simple questions about natural imagery.

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(NeurIPS24) NaturalBench: Evaluating Vision-Language Models on Natural Adversarial Samples

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You can learn how to use and evaluate NaturalBench by reviewing the simple examples in example.py.

Citation Information

@inproceedings{naturalbench,
  title={NaturalBench: Evaluating Vision-Language Models on Natural Adversarial Samples},
  author={Li, Baiqi and Lin, Zhiqiu and Peng, Wenxuan and Nyandwi, Jean de Dieu and Jiang, Daniel and Ma, Zixian and Khanuja, Simran and Krishna, Ranjay and Neubig, Graham and Ramanan, Deva},
  booktitle={The Thirty-eight Conference on Neural Information Processing Systems Datasets and Benchmarks Track},
  year={2024},
  url={https://openreview.net/forum?id=Dx88A9Zgnv}
}

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πŸš€ [NeurIPS24] Make Vision Matter in Visual-Question-Answering (VQA)! Introducing NaturalBench, a vision-centric VQA benchmark (NeurIPS'24) that challenges vision-language models with simple questions about natural imagery.

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