From Papers to Mechanisms: An Evidence-Grounded Knowledge Substrate for Scientific Language Models

Excerpt

arXiv:2610.06248v1 Announce Type: new Abstract: Scientific language models often access literature through untyped text chunks, which fragment the functional and evidential structure required for mechanism-rich questions. We introduce an evidence-grounded mechanism knowledge substrate that organizes scientific literature into provenance-linked evidence units, role-typed entities, and directed mechanism paths. We instantiate it as MS$^3$, a Material-Sensor-Signal-System schema for conductive-fibe