LightGBM models on citation and diversity features predict exogenous diffusion of quantum computing concepts with R² up to 0.78 while endogenous reinforcement remains largely unpredictable after growth controls, with replications in other fields.
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EstGraph benchmark evaluates LLMs on estimating properties of very large graphs from random-walk samples that fit in context limits.
A two-stage LightGBM model on 59 features from concept networks forecasts link formation and intensity with ROC-AUC 0.95-0.967 across domains.
Software engineering research faces four structural breakdowns in knowledge accumulation—isolated papers, lost context, untracked claims, and novelty incentives—and requires new principles for structured, provenance-aware, evolving research artifacts.
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Forecasting Conceptual Diffusion in Science: The Case of Quantum Computing
LightGBM models on citation and diversity features predict exogenous diffusion of quantum computing concepts with R² up to 0.78 while endogenous reinforcement remains largely unpredictable after growth controls, with replications in other fields.
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Explainable Forecasting of Scientific Breakthroughs from Concept Network Dynamics
A two-stage LightGBM model on 59 features from concept networks forecasts link formation and intensity with ROC-AUC 0.95-0.967 across domains.