arXiv — NLP / Computation & Language · · 3 min read

The Scientific Contribution Graph: Automated Literature-based Technological Roadmapping at Scale

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Computer Science > Computation and Language

arXiv:2605.15011 (cs)
[Submitted on 14 May 2026]

Title:The Scientific Contribution Graph: Automated Literature-based Technological Roadmapping at Scale

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Abstract:Scientific contributions rarely develop in isolation, but instead build upon prior discoveries. We formulate the task of automated technological roadmapping as extracting scientific contributions from scholarly articles and linking them to their prerequisites. We present the Scientific Contribution Graph, a large-scale AI/NLP-domain resource containing 2 million detailed scientific contributions extracted from 230k open-access papers and connected by 12.5 million prerequisite edges. We further introduce scientific prerequisite prediction, a scientific discovery task in which models predict which existing technologies can enable future discoveries, and show that contemporary models are rapidly improving on this task, reaching 0.48 MAP when evaluated using temporally filtered backtesting. We anticipate technological roadmapping resources such as this will support scientific impact assessment and automated scientific discovery.
Comments: 8 pages, 4 figures
Subjects: Computation and Language (cs.CL)
Cite as: arXiv:2605.15011 [cs.CL]
  (or arXiv:2605.15011v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2605.15011
arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Peter Jansen [view email]
[v1] Thu, 14 May 2026 16:12:12 UTC (515 KB)
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