UniversalCEFR/readme_ru

该数据集已被索引在UniversalCEFR中。转换后的版本（JSON格式）保留了原始数据集的许可证。所有权和版权归原作者和/或数据集论文作者所有。使用此转换数据集时，必须引用以下内容：数据集许可证：cc-by-nc-sa-4.0。数据集仓库：https://github.com/tareknaous/readme。原始数据集论文：Tarek Naous, Michael J Ryan, Anton Lavrouk, Mohit Chandra, 和 Wei Xu. 2024. ReadMe++：针对多领域可读性评估的多语言语言模型基准测试。在2024年自然语言处理实证方法会议论文集中，第12230-12266页，美国佛罗里达州迈阿密。计算语言学协会。

This dataset has been indexed in the UniversalCEFR. The transformed version (in JSON format) retains the same license as the original dataset. Ownership and copyright remain with the original creators and/or dataset paper authors. If you use this transformed dataset, you must cite the following: Dataset License: cc-by-nc-sa-4.0. Dataset Repository: https://github.com/tareknaous/readme. Original Dataset Paper: Tarek Naous, Michael J Ryan, Anton Lavrouk, Mohit Chandra, and Wei Xu. 2024. ReadMe++: Benchmarking Multilingual Language Models for Multi-Domain Readability Assessment. In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, pages 12230–12266, Miami, Florida, USA. Association for Computational Linguistics.