| language: | |
| - en | |
| license: mit | |
| size_categories: | |
| - 1M<n<10M | |
| task_categories: | |
| - visual-question-answering | |
| - image-text-to-text | |
| pretty_name: ABC-Pretraining-Data | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: train | |
| path: data/train-* | |
| dataset_info: | |
| features: | |
| - name: caption | |
| dtype: string | |
| - name: url | |
| dtype: string | |
| - name: id | |
| dtype: int64 | |
| - name: image | |
| dtype: string | |
| - name: negatives | |
| sequence: int64 | |
| splits: | |
| - name: train | |
| num_bytes: 2289772991 | |
| num_examples: 2252041 | |
| download_size: 1855548818 | |
| dataset_size: 2289772991 | |
| tags: | |
| - visual | |
| ## ABC Pretraining Data | |
| <!-- Provide a quick summary of the dataset. --> | |
| This the the pretraining data for ABC. This dataset is derived from Google's [Conceptual Captions](https://ai.google.com/research/ConceptualCaptions/) dataset. | |
| The each item in the dataset contain a URL where the corresponding image can be downloaded. Full dataaset is ~300 GB of images. | |
| ## Paper and Website | |
| For more information, please refer to [Website](https://tiger-ai-lab.github.io/ABC/). | |
| ## Citation | |
| ``` | |
| @misc{schneider2025abcachievingbettercontrol, | |
| title={ABC: Achieving Better Control of Multimodal Embeddings using VLMs}, | |
| author={Benjamin Schneider and Florian Kerschbaum and Wenhu Chen}, | |
| year={2025}, | |
| eprint={2503.00329}, | |
| archivePrefix={arXiv}, | |
| primaryClass={cs.CV}, | |
| url={https://arxiv.org/abs/2503.00329}, | |
| } | |
| ``` |