TIGER-Lab/ScholarCopilot-Data-v1

ScholarCopilot-Data-v1数据集包含Scholar Copilot项目的语料数据和嵌入向量。Scholar Copilot通过自动文本完成和智能引用建议来提高学术写作效率。该数据集基于一个70亿参数的先进语言模型，该模型在完整的Arxiv论文语料库上训练，能够进行上下文敏感的引用和内容生成决策。数据集的主要功能包括下一句预测、按需引用建议和完整章节自动完成，目前主要关注学术论文的引言和相关工作部分。

ScholarCopilot-Data-v1 contains the corpus data and embedded vectors of the Scholar Copilot project. Scholar Copilot enhances academic writing efficiency through automatic text completion and intelligent citation suggestions. The dataset is based on a state-of-the-art 7-billion-parameter language model trained on the complete Arxiv paper corpus, capable of making context-sensitive decisions on citations and content generation. Key features of the dataset include next-sentence prediction, on-demand citation suggestions, and full-section auto-completion, currently focusing on the introduction and related work sections of academic papers.