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YAML Metadata Warning: The task_categories "text2text-generation" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other

Perspective-Taking Dataset

Dataset Description

This dataset contains image-question pairs for perspective-taking tasks.

Dataset Statistics

  • Training samples: 218
  • Testing samples: 25
  • Total samples: 243
  • Concepts: concept_10_image, concept_10_multiimage

Dataset Structure

The dataset is organized into train and test splits for each concept. Each sample consists of:

  • An image file (or multiple images)
  • A question about the image
  • An answer to the question (when available)

Data Fields

  • id: Question identifier
  • concept: The concept category the question belongs to
  • question: The question text from question.txt
  • answer: The answer text from answer.txt (when available)
  • image: Filename of the primary image
  • additional_images: Additional images if present
  • additional_text: Additional text files with their content
  • split: Train or test split

Usage 

from datasets import load_dataset

# Load the dataset
dataset = load_dataset("path/to/dataset")

# Access examples
sample = dataset["train"][0]
print(f"Question: {sample['question']}")
print(f"Answer: {sample.get('answer', 'No answer available')}")
print(f"Image path: {sample['image']}")

# If the sample has additional images
if 'additional_images' in sample and sample['additional_images']:
    print(f"Additional images: {sample['additional_images']}")

Citation 

@article{gao2024vision,
  title={Vision Language Models See What You Want but not What You See},
  author={Gao, Qingying and Li, Yijiang and Lyu, Haiyun and Sun, Haoran and Luo, Dezhi and Deng, Hokin},
  journal={arXiv preprint arXiv:2410.00324},
  year={2024}
}

arxiv link: https://arxiv.org/abs/2410.00324

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