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sentence1
imagewidth (px) 448
448
| sentence2
imagewidth (px) 448
448
| score
float64 0
5
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2.5 |
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3.6 |
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5 |
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4.2 |
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1.5 |
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1.8 |
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3.5 |
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2.2 |
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2.2 |
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1.714 |
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1.714 |
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5 |
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0.6 |
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4.4 |
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2 |
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1.8 |
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4.4 |
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3.6 |
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3.6 |
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1.2 |
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2.4 |
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0.2 |
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4.2 |
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4.4 |
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2.25 |
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2 |
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0.75 |
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2.2 |
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0.8 |
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2.2 |
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3.2 |
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4.8 |
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1.4 |
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4.25 |
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3.4 |
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0.533 |
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0.4 |
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1.2 |
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5 |
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0.538 |
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3.75 |
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3 |
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3.6 |
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0.5 |
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1.5 |
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0.8 |
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0.8 |
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0.6 |
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4.4 |
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1.75 |
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0.4 |
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1.4 |
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0.4 |
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0.8 |
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2 |
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0.133 |
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4 |
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0.267 |
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3.4 |
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1.2 |
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5 |
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0 |
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3.8 |
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0.75 |
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3.4 |
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0 |
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0.2 |
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4 |
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0.5 |
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3.8 |
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2.4 |
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4.75 |
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0 |
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3.75 |
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2.6 |
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0 |
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0.75 |
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0 |
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3.8 |
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2.8 |
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0 |
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0.8 |
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3 |
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1 |
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0 |
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1 |
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3.4 |
||
5 |
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2.333 |
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1.4 |
||
0.75 |
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3.538 |
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0.8 |
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3.5 |
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2 |
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4.75 |
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4 |
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4.5 |
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1.5 |
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2.4 |
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Dataset Summary
This dataset is rendered to images from STS-benchmark. We envision the need to assess vision encoders' abilities to understand texts. A natural way will be assessing them with the STS protocols, with texts rendered into images.
Examples of Use
Load English train Dataset:
from datasets import load_dataset
dataset = load_dataset("Pixel-Linguist/rendered-stsb", name="en", split="train")
Load Chinese dev Dataset:
from datasets import load_dataset
dataset = load_dataset("Pixel-Linguist/rendered-stsb", name="zh", split="dev")
Languages
de, en, es, fr, it, nl, pl, pt, ru, zh
Citation Information
@article{xiao2024pixel,
title={Pixel Sentence Representation Learning},
author={Xiao, Chenghao and Huang, Zhuoxu and Chen, Danlu and Hudson, G Thomas and Li, Yizhi and Duan, Haoran and Lin, Chenghua and Fu, Jie and Han, Jungong and Moubayed, Noura Al},
journal={arXiv preprint arXiv:2402.08183},
year={2024}
}
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