JoeyCheng/story_analogy
收藏资源简介：
--- license: mit language: - en pretty_name: StoryAnalogy size_categories: - 1K<n<10K --- <h1 align="center">StoryAnalogy: Deriving Story-level Analogies from Large Language Models to Unlock Analogical Understanding</h1> <p align="center"> <a href="https://arxiv.org/abs/2310.12874"><img src="https://img.shields.io/badge/arXiv-2310.12874-b31b1b.svg" alt="Paper" style="display:inline"></a> <a href="https://aclanthology.org/2023.emnlp-main.706/"> <img alt="License" src="https://img.shields.io/static/v1?label=Pub&message=EMNLP%2723&color=blue" style="display:inline"> </a> <a href="https://github.com/LFhase/PAIR"><img src="https://img.shields.io/badge/-Github-grey?logo=github" alt="Github" style="display:inline"></a> <a href="https://github.com/LFhase/PAIR/blob/main/LICENSE"> <img alt="License" src="https://img.shields.io/github/license/LFhase/PAIR?color=blue" style="display:inline"> </a> <a href="https://github.com/loginaway/StoryAnalogy/blob/main/raw/Poster%20-%20StoryAnalogy%20Deriving%20Story-level%20Analogies%20from%20Large%20Language%20Models%20to%20Unlock%20Analogical%20Understanding.pdf"> <img src="https://img.shields.io/badge/Poster-grey?logo=airplayvideo&logoColor=white" alt="Poster" style="display:inline"></a> </div> This is the StoryAnalogy dataset in the EMNLP'23 paper: *[StoryAnalogy: Deriving Story-level Analogies from Large Language Models to Unlock Analogical Understanding](https://arxiv.org/abs/2310.12874)*. If you use this research, please cite us: ```bibtex @inproceedings{jiayang2023storyanalogy, title={StoryAnalogy: Deriving Story-level Analogies from Large Language Models to Unlock Analogical Understanding}, author={Jiayang, Cheng and Qiu, Lin and Chan, Tsz and Fang, Tianqing and Wang, Weiqi and Chan, Chunkit and Ru, Dongyu and Guo, Qipeng and Zhang, Hongming and Song, Yangqiu and others}, booktitle={Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing}, pages={11518--11537}, year={2023} } ```
license: MIT协议 language: - 英语 pretty_name: StoryAnalogy size_categories: - 样本量介于1000至10000之间 <h1 align="center">StoryAnalogy：从大语言模型（Large Language Model）中提取故事级类比以解锁类比理解能力</h1> <p align="center"> <a href="https://arxiv.org/abs/2310.12874"><img src="https://img.shields.io/badge/arXiv-2310.12874-b31b1b.svg" alt="论文链接" style="display:inline"></a> <a href="https://aclanthology.org/2023.emnlp-main.706/"> <img alt="会议发表" src="https://img.shields.io/static/v1?label=Pub&message=EMNLP%2723&color=blue" style="display:inline"> </a> <a href="https://github.com/LFhase/PAIR"><img src="https://img.shields.io/badge/-Github-grey?logo=github" alt="GitHub仓库" style="display:inline"></a> <a href="https://github.com/LFhase/PAIR/blob/main/LICENSE"> <img alt="许可证" src="https://img.shields.io/github/license/LFhase/PAIR?color=blue" style="display:inline"></a> <a href="https://github.com/loginaway/StoryAnalogy/blob/main/raw/Poster%20-%20StoryAnalogy%20Deriving%20Story-level%20Analogies%20from%20Large%20Language%20Models%20to%20Unlock%20Analogical%20Understanding.pdf"> <img src="https://img.shields.io/badge/Poster-grey?logo=airplayvideo&logoColor=white" alt="会议海报" style="display:inline"></a> </div> 本数据集即来自EMNLP 2023会议论文《StoryAnalogy：从大语言模型中提取故事级类比以解锁类比理解能力》中的StoryAnalogy数据集。 若您在研究中使用本数据集，请引用以下文献： bibtex @inproceedings{jiayang2023storyanalogy, title={StoryAnalogy: Deriving Story-level Analogies from Large Language Models to Unlock Analogical Understanding}, author={Jiayang, Cheng and Qiu, Lin and Chan, Tsz and Fang, Tianqing and Wang, Weiqi and Chan, Chunkit and Ru, Dongyu and Guo, Qipeng and Zhang, Hongming and Song, Yangqiu and others}, booktitle={Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing}, pages={11518--11537}, year={2023} }
数据集概述
数据集名称
- StoryAnalogy
数据集描述
- StoryAnalogy 是一个用于从大型语言模型中提取故事级类比以解锁类比理解的数据集。
数据集规模
- 大小类别：1K<n<10K
数据集语言
- 语言：英语
数据集相关出版物
- 论文：StoryAnalogy: Deriving Story-level Analogies from Large Language Models to Unlock Analogical Understanding
- 会议：EMNLP23
数据集许可证
- 许可证：MIT
引用信息
bibtex @inproceedings{jiayang2023storyanalogy, title={StoryAnalogy: Deriving Story-level Analogies from Large Language Models to Unlock Analogical Understanding}, author={Jiayang, Cheng and Qiu, Lin and Chan, Tsz and Fang, Tianqing and Wang, Weiqi and Chan, Chunkit and Ru, Dongyu and Guo, Qipeng and Zhang, Hongming and Song, Yangqiu and others}, booktitle={Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing}, pages={11518--11537}, year={2023} }
