English(EN) RelPrism: A Multi-Faceted Pre-training Framework with Self-Generated Tasks for Relational Databases

RelPrism框架通过自生成任务增强关系数据库学习

作者 PulseAugur 编辑部 · [1 个来源] · 2026-05-25 04:00

研究人员开发了RelPrism，一个用于关系数据库自监督学习的新框架。这种多方面方法从不同角度构建内在、关系和混合属性，并使用多粒度聚类创建伪任务池。通过将表示暴露于多样化的信息和粒度，RelPrism增强了下游任务的适应性。实验表明，与现有方法相比，在分类和回归性能方面有了显著的提高。 AI

影响引入了一个新的自监督学习框架，提高了关系数据库任务的性能，可能使数据分析和预测系统受益。

排序理由该集群包含一篇详细介绍关系数据库学习新框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

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本文如何被排名

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Newsworthiness bucket: Tool; 该集群包含一篇详细介绍关系数据库学习新框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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arXiv cs.LG TIER_1 English(EN) · Jinyu Yang, Cheng Yang, Junze Chen, Zedi Liu, Muhan Zhang, Hanyang Peng, Chuan Shi · 2026-05-25 04:00

RelPrism：一个具有自生成任务的多方面关系数据库预训练框架

arXiv:2605.23241v1 Announce Type: new Abstract: Relational databases (RDBs) remain the cornerstone of modern data systems and support diverse predictive tasks. Recent relational deep learning (RDL) methods enable end-to-end prediction by converting RDBs into graphs, where rows ar…