SOURCE-LINKED INTELLIGENCE

SPARK: Skeleton-Guided Reasoning Synthesis from Large-Scale Scientific Literature

arXiv · AI, language, vision and robotics · article · Aug 31, 2026 · UTC

Scientific reasoning remains challenging for open-source models, largely due to the lack of high-quality scientific reasoning data. Existing datasets are often dominated by factual recall or formulaic problem solving, with limited emphasis on mechanism understanding, evidence-grounded reasoning, and hypothesis evaluation. To address this, we introduce SPARK (Scientific Paper Abstracted Reasoning sKeleton), a paper-oriented synthesis framework built on Sci-Base, a large-scale corpus of research papers spanning 10 scientific disciplines. Instead of directly converting papers into question-answer

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