SimulRAG: Simulator-based RAG for Grounding LLMs in Long-form Scientific QA
The SimulRAG framework grounds large language models in scientific knowledge by querying simulators instead of just text documents. The hosts discuss how the system uses uncertainty estimation and boundary assessment to selectively verify claims, significantly improving factuality and informativeness in fields like climate science, epidemiology, and urban planning.