{
 "id": "tangzx2024/CoLT-Drive",
 "owner": "tangzx2024",
 "name": "CoLT-Drive",
 "downloads": 1533,
 "likes": 0,
 "last_modified": "2026-09-23T15:00:14.000Z",
 "stated_licence": "apache-2.0",
 "stated_from": "tag",
 "licence_name": null,
 "licence_link": null,
 "file_licence": null,
 "licence_files": [],
 "sources": [],
 "gated": false,
 "tasks": [
  "visual-question-answering"
 ],
 "citation": "@inproceedings{tang2026coltdrive,\n  title     = {CoLT-Drive: Counterfactual Long-Tail Benchmarking and Knowledge-Preserving Adaptation for Driving Affordance Prediction},\n  author    = {Tang, Zhengxu and Cui, Guofeng and Gong, Ziyu and Zhang, Xiaozhou and Deng, Ruifeng and Qi, Chengzhi and Chen, Ke and Patil, Sachin and Xiao, Tianjun and Liu, Langechuan and Wang, Pichao},\n  booktitle = {Findings of the Association for Computational Linguistics: EMNLP 2026},\n  year      = {2026},\n  url       = {https://arxiv.org/abs/2609.00242}\n}",
 "signal": "permissive",
 "reason": "The declared licence (apache-2.0) is classified as permissive.",
 "revision": "684d299bc8974731513fc2599b2f4dccb7cfc67c",
 "stated_evidence": "https://huggingface.co/datasets/tangzx2024/CoLT-Drive/blob/684d299bc8974731513fc2599b2f4dccb7cfc67c/README.md",
 "file_evidence": "https://huggingface.co/datasets/tangzx2024/CoLT-Drive/tree/684d299bc8974731513fc2599b2f4dccb7cfc67c",
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}