{
 "id": "kmsgk/BEST",
 "owner": "kmsgk",
 "name": "BEST",
 "downloads": 241,
 "likes": 0,
 "last_modified": "2026-05-29T11:19:56.000Z",
 "stated_licence": "mit",
 "stated_from": "tag",
 "licence_name": null,
 "licence_link": null,
 "file_licence": null,
 "licence_files": [],
 "sources": [],
 "gated": false,
 "tasks": [
  "text-generation"
 ],
 "citation": "@inproceedings{shen2026best,\n  title = {BEST: Benchmarking Efficiency in Space and Time for LLM-Generated Code},\n  author = {Shen, Aocheng and Zhang, Boyu and Li, Jiaze and Ma, Ruixuan and Zhang, Qiankun and Wang, Jing and Yuan, Bin and Liu, Shenghao and Deng, Xianjun},\n  booktitle = {Proceedings of the 43rd International Conference on Machine Learning},\n  year = {2026}\n}",
 "signal": "permissive",
 "reason": "The declared licence (mit) is classified as permissive.",
 "revision": "0475ba76304c6e09a752758100a1e661bf301546",
 "stated_evidence": "https://huggingface.co/datasets/kmsgk/BEST/blob/0475ba76304c6e09a752758100a1e661bf301546/README.md",
 "file_evidence": "https://huggingface.co/datasets/kmsgk/BEST/tree/0475ba76304c6e09a752758100a1e661bf301546",
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}