| dataset_info: | |
| features: | |
| - name: sentence1 | |
| dtype: image | |
| - name: sentence2 | |
| dtype: image | |
| - name: score | |
| dtype: float64 | |
| splits: | |
| - name: test | |
| num_bytes: 13930539.5 | |
| num_examples: 1186 | |
| download_size: 10439022 | |
| dataset_size: 13930539.5 | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: test | |
| path: data/test-* | |
| ### Dataset Summary | |
| This dataset is rendered to images from STS-16. 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 test split: | |
| ```python | |
| from datasets import load_dataset | |
| dataset = load_dataset("Pixel-Linguist/rendered-sts16", split="test") | |
| ``` | |
| ### Languages | |
| English-only; for multilingual and cross-lingual datasets, see `Pixel-Linguist/rendered-stsb` and `Pixel-Linguist/rendered-sts17` | |
| ### 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} | |
| } | |
| ``` |