SciAtlas: A Large-Scale Knowledge Graph for Automated Scientific Research
SciAtlas is a large-scale knowledge graph aimed at enhancing automated scientific research. It integrates over 43 million academic papers and provides a structured framework for navigating complex interdisciplinary connections. The tool is designed to reduce reasoning costs and improve the efficiency of literature reviews and research trend synthesis.
- ▪SciAtlas integrates over 43 million papers from 26 disciplines, creating a comprehensive academic resource.
- ▪The knowledge graph features a neuro-symbolic retrieval algorithm that enhances the discovery of logical associations.
- ▪Key applications of SciAtlas include literature review, automated research trend synthesis, and academic trajectory exploration.
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Computer Science > Artificial Intelligence arXiv:2605.22878 (cs) [Submitted on 20 May 2026] Title:SciAtlas: A Large-Scale Knowledge Graph for Automated Scientific Research Authors:Shuofei Qiao, Yunxiang Wei, Jiazheng Fan, Bin Wu, Busheng Zhang, Mengru Wang, Yuqi Zhu, Ningyu Zhang, Keyan Ding, Qiang Zhang, Huajun Chen View a PDF of the paper titled SciAtlas: A Large-Scale Knowledge Graph for Automated Scientific Research, by Shuofei Qiao and 10 other authors View PDF HTML (experimental) Abstract:The exponential growth of global academic output has confronted researchers and AI agents with an unprecedented ``information explosion,'' where fragmented and unstructured knowledge organization impedes deep interdisciplinary integration.
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