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--- |
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dataset_info: |
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features: |
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- name: image |
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dtype: image |
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- name: AnnotatorId |
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dtype: string |
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- name: ImgId |
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dtype: string |
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- name: caption |
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dtype: string |
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- name: Impact |
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dtype: float64 |
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- name: image_description |
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dtype: string |
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- name: image_impression |
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dtype: string |
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- name: image_aesthetic_eval |
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dtype: string |
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- name: image_url |
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dtype: string |
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- name: source |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 2366953929.024 |
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num_examples: 1352 |
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download_size: 2214475090 |
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dataset_size: 2366953929.024 |
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license: cc-by-sa-4.0 |
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task_categories: |
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- image-to-text |
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- visual-question-answering |
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language: |
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- en |
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tags: |
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- art |
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pretty_name: Impressions |
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size_categories: |
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- 1K<n<10K |
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--- |
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# Dataset Card for "Impressions" |
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## Overview |
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The Impressions dataset is a multimodal benchmark that consists of 4,100 unique annotations and over 1,375 image-caption pairs from the photography domain. Each annotation explores (1) the aesthetic impactfulness of a photograph, (2) image descriptions in which pragmatic inferences are welcome, (3) emotions/thoughts/beliefs that the photograph may inspire, and (4) the aesthetic elements that elicited the expressed impression. |
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EMNLP 2023 | [Paper](https://arxiv.org/abs/2310.17887) |
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## Additional Data |
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The Impressions dataset comes with more information that just image annotations on questions pertaining to *Pragmatic Description*, *Perception*, and *Aesthetic Evaluation*. For annotator personality and demographic metadata, as well as all *Aesthetic Impact* annotations, please see our [git repository](https://github.com/SALT-NLP/Impressions)! |
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[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) |
