{
 "id": "kd7/graid-bdd",
 "owner": "kd7",
 "name": "graid-bdd",
 "downloads": 5320,
 "likes": 2,
 "last_modified": "2025-10-29T01:01:22.000Z",
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 "gated": false,
 "tasks": [
  "visual-question-answering",
  "object-detection",
  "image-text-to-text"
 ],
 "citation": "@article{graid2025spatial,\n  title={GRAID: Enhancing Spatial Reasoning of VLMs Through High-Fidelity Data Generation},\n  author={{Anonymous}},\n  journal={arXiv preprint arXiv:2510.22118},\n  year={2025},\n  url={https://huggingface.co/papers/2510.22118}\n}\n\n@dataset{graid_bdd,\n    title={GRAID BDD100K Question-Answer Dataset},\n    author={GRAID Framework},\n    year={2025},\n    note={Generated using GRAID: Generating Reasoning questions from Analysis of Images via Discriminative artificial intelligence}\n}\n\n@INPROCEEDINGS{9156329,\n    author={Yu, Fisher and Chen, Haofeng and Wang, Xin and Xian, Wenqi and Chen, Yingying and Liu, Fangchen and Madhavan, Vashisht and Darrell, Trevor},\n    booktitle={2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, \n    title={BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning}, \n    year={2020},\n    volume={},\n    number={},\n    pages={2633-2642},\n    keywords={Task analysis;Visualization;Roads;Image segmentation;Meteorology;Training;Benchmark testing},\n    doi={10.1109/CVPR42600.2020.00271}\n}",
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