{
 "id": "agentlans/lime-nlp-difficulty",
 "owner": "agentlans",
 "name": "lime-nlp-difficulty",
 "downloads": 26,
 "likes": 0,
 "last_modified": "2025-11-19T10:28:19.000Z",
 "stated_licence": "mit",
 "stated_from": "tag",
 "licence_name": null,
 "licence_link": null,
 "file_licence": null,
 "licence_files": [],
 "sources": [],
 "gated": false,
 "tasks": [
  "text-classification"
 ],
 "citation": "@misc{shi2025efficientreinforcementfinetuningadaptive,\n  title={Efficient Reinforcement Finetuning via Adaptive Curriculum Learning}, \n  author={Taiwei Shi and Yiyang Wu and Linxin Song and Tianyi Zhou and Jieyu Zhao},\n  year={2025},\n  eprint={2504.05520},\n  archivePrefix={arXiv},\n  primaryClass={cs.LG},\n  url={https://arxiv.org/abs/2504.05520}, \n}",
 "signal": "permissive",
 "reason": "The declared licence (mit) is classified as permissive.",
 "revision": "a0cb059b848b2fe578e1c12dfd50b8ee83873d4f",
 "stated_evidence": "https://huggingface.co/datasets/agentlans/lime-nlp-difficulty/blob/a0cb059b848b2fe578e1c12dfd50b8ee83873d4f/README.md",
 "file_evidence": "https://huggingface.co/datasets/agentlans/lime-nlp-difficulty/tree/a0cb059b848b2fe578e1c12dfd50b8ee83873d4f",
 "card_nc": false
}