AmberLJC/ai-paper-intellectual-lineage-2023

该数据集包含了2022-2024年间发表的20篇有影响力的AI研究论文及其知识谱系，每篇论文都追溯了1-2篇关键的前期工作，并包含了一段约300字的段落，解释了当前工作与其基础之间的关系。数据集的目的包括帮助研究人员、学生、从业者和AI系统理解AI研究的演变和基础。数据集的结构包括论文标题、作者、年份、发表场所、算法类型、关键创新、前期工作标题、作者、年份、贡献以及知识谱系段落等字段。数据集涵盖了多个AI领域的突破性算法，如大型语言模型、注意力机制、计算机视觉等。论文的选择基于算法创新、发表场所和影响力。

This dataset contains 20 impactful AI research papers published between 2022-2024, along with their intellectual lineage - tracing 1-2 key prior works each paper builds upon, and a ~300-word paragraph explaining the relationship between the current work and its foundations. The purpose of the dataset is to help researchers, students, practitioners, and AI systems understand the evolution and foundations of AI research. The dataset structure includes fields such as paper title, author, year, publication venue, algorithm type, key innovation, prior work titles, authors, years, contributions, and intellectual lineage paragraphs. The dataset covers breakthrough algorithms in multiple AI domains, such as large language models, attention mechanisms, and computer vision. Papers were selected based on algorithmic innovation, publication venue, and impact.