{
 "id": "kd7/graid-bdd100k",
 "owner": "kd7",
 "name": "graid-bdd100k",
 "downloads": 338,
 "likes": 0,
 "last_modified": "2025-10-29T01:02:52.000Z",
 "stated_licence": "bsd-3-clause",
 "stated_from": "tag",
 "licence_name": null,
 "licence_link": null,
 "file_licence": null,
 "licence_files": [],
 "sources": [],
 "gated": false,
 "tasks": [
  "visual-question-answering",
  "object-detection",
  "image-text-to-text"
 ],
 "citation": "@article{GRAID_paper,\n    title={GRAID: Enhancing Spatial Reasoning of VLMs Through High-Fidelity Data Generation},\n    author={{GRAID Framework Authors}},\n    year={2025},\n    journal={Hugging Face Paper},\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}",
 "signal": "permissive",
 "reason": "The declared licence (bsd-3-clause) is classified as permissive.",
 "revision": "c99b17c1ae956749de9275d3f29cb403f45c9503",
 "stated_evidence": "https://huggingface.co/datasets/kd7/graid-bdd100k/blob/c99b17c1ae956749de9275d3f29cb403f45c9503/README.md",
 "file_evidence": "https://huggingface.co/datasets/kd7/graid-bdd100k/tree/c99b17c1ae956749de9275d3f29cb403f45c9503",
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}