metadata

language:
  - en
dataset_info:
  features:
    - name: id
      dtype: string
    - name: instance_id
      dtype: int64
    - name: question
      dtype: string
    - name: answer
      list:
        dtype: string
    - name: A
      dtype: string
    - name: B
      dtype: string
    - name: C
      dtype: string
    - name: D
      dtype: string
    - name: category
      dtype: string
    - name: img
      dtype: image
configs:
  - config_name: 1_correct
    data_files:
      - split: validation
        path: 1_correct/validation/0000.parquet
      - split: test
        path: 1_correct/test/0000.parquet
  - config_name: 1_correct_var
    data_files:
      - split: validation
        path: 1_correct_var/validation/0000.parquet
      - split: test
        path: 1_correct_var/test/0000.parquet
  - config_name: n_correct
    data_files:
      - split: validation
        path: n_correct/validation/0000.parquet
      - split: test
        path: n_correct/test/0000.parquet

DARE

DARE (Diverse Visual Question Answering with Robustness Evaluation) is a carefully created and curated multiple-choice VQA benchmark. DARE evaluates VLM performance on five diverse categories and includes four robustness-oriented evaluations based on the variations of:

prompts
the subsets of answer options
the output format
the number of correct answers.

The validation split of the dataset contains images, questions, answer options, and correct answers. We are not publishing the correct answers for the test split to prevent contamination.

Load the Dataset

To use the dataset use the huggingface datasets library:

from datasets import load_dataset

# Load the dataset
subset = "1_correct" # Change to the subset that you want to use
dataset = load_dataset("cambridgeltl/DARE", subset)

Citation

If you use this dataset, please cite our paper:

@article{sterz2024dare,
  title={DARE: Diverse Visual Question Answering with Robustness Evaluation},
  author={Sterz, Hannah and Pfeiffer, Jonas and Vuli{\'c}, Ivan},
  journal={arXiv preprint arXiv:2409.18023},
  year={2024}
}