{
 "id": "LARK-Lab/CodeScalerPair-51K",
 "owner": "LARK-Lab",
 "name": "CodeScalerPair-51K",
 "downloads": 72,
 "likes": 2,
 "last_modified": "2026-02-23T01:32:35.000Z",
 "stated_licence": "mit",
 "stated_from": "tag",
 "licence_name": null,
 "licence_link": null,
 "file_licence": null,
 "licence_files": [],
 "sources": [],
 "gated": false,
 "tasks": [],
 "citation": "@misc{zhu2026codescalerscalingcodellm,\n      title={CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models}, \n      author={Xiao Zhu and Xinyu Zhou and Boyu Zhu and Hanxu Hu and Mingzhe Du and Haotian Zhang and Huiming Wang and Zhijiang Guo},\n      year={2026},\n      eprint={2602.17684},\n      archivePrefix={arXiv},\n      primaryClass={cs.LG},\n      url={https://arxiv.org/abs/2602.17684}, \n}",
 "signal": "permissive",
 "reason": "The declared licence (mit) is classified as permissive.",
 "revision": "f171a14323c0a7858261cfce2d4e8a0ab177c06e",
 "stated_evidence": "https://huggingface.co/datasets/LARK-Lab/CodeScalerPair-51K/blob/f171a14323c0a7858261cfce2d4e8a0ab177c06e/README.md",
 "file_evidence": "https://huggingface.co/datasets/LARK-Lab/CodeScalerPair-51K/tree/f171a14323c0a7858261cfce2d4e8a0ab177c06e",
 "card_nc": false
}