metadata
task_categories:
- visual-question-answering
language:
- en
pretty_name: Vision-Flan
size_categories:
- 100K<n<1M
π Vision-Flan Dataset
vision-flan_191-task-1k is a human-labeled visual instruction tuning dataset consisting of 191 diverse tasks and 1,000 examples for each task. It is constructed for visual instruction tuning and for building large-scale vision-language models.
Paper or blog for more information:
https://github.com/VT-NLP/MultiInstruct/
https://vision-flan.github.io/
Paper coming soon π
Citation
Paper coming soon π. If you use Vision-Flan, please use the following cites:
@misc{visionFlan2023,
title = {Vision-Flan:Scaling Visual Instruction Tuning},
url = {https://vision-flan.github.io/},
author = {Zhiyang Xu and Trevor Ashby and Chao Feng and Rulin Shao and Ying Shen and Di Jin and Qifan Wang and Lifu Huang},
month = {Sep},
year = {2023}
}
@inproceedings{DBLP:conf/acl/XuSH23,
author = {Zhiyang Xu and Ying Shen and Lifu Huang},
editor = {Anna Rogers and Jordan L. Boyd{-}Graber and Naoaki Okazaki},
title = {MultiInstruct: Improving Multi-Modal Zero-Shot Learning via Instruction Tuning},
booktitle = {Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), {ACL} 2023, Toronto, Canada, July 9-14, 2023},
pages = {11445--11465},
publisher = {Association for Computational Linguistics},
year = {2023},
url = {https://doi.org/10.18653/v1/2023.acl-long.641},
doi = {10.18653/v1/2023.acl-long.641},
timestamp = {Thu, 10 Aug 2023 12:35:59 +0200},
biburl = {https://dblp.org/rec/conf/acl/XuSH23.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
License:
Please carefully check the licenses for all the datasets on this page before use.
Contact:
If you have any questions or concerns please contact us at [email protected] .