AI RESEARCH
From Experiments to Expertise: Scientific Knowledge Consolidation for AI-Driven Computational Research
arXiv CS.AI
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ArXi:2603.13191v1 Announce Type: cross While large language models (LLMs) have transformed AI agents into proficient executors of computational materials science, performing a hundred simulations does not make a researcher. What distinguishes research from routine execution is the progressive accumulation of knowledge -- learning which approaches fail, recognizing patterns across systems, and applying understanding to new problems. However, the prevailing paradigm in AI-driven computational science treats each execution in isolation, largely discarding hard-won insights between runs.