Knowledge Boundary Probing and Demand-Guided Intervention for LLM-Based Power System Code Generation 事件

Knowledge Boundary Probing and Demand-Guided Intervention for LLM-Based Power System Code Generation arXiv:2605.31478v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to automate power-system analysis, but many utilities and energy-research labs require on-premise serving for confidentiality, regulatory, reproducibility, and cost reasons. This makes the reliability of open-weight models a deployment issue. We show that first-pass failures in power-system code