PowerCodeBench and a boundary-aware intervention raise LLM accuracy on power-system code generation by 32-56 points across ten open-weight models and four commercial APIs on a 2,000-task benchmark.
Large language models meet energy systems: Opportunities, challenges, and future perspectives.Applied Energy, 403:127076, 2026
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Knowledge Boundary Probing and Demand-Guided Intervention for LLM-Based Power System Code Generation
PowerCodeBench and a boundary-aware intervention raise LLM accuracy on power-system code generation by 32-56 points across ten open-weight models and four commercial APIs on a 2,000-task benchmark.