Introduces the Power Systems Agent Benchmark with 41 task families across eight power engineering areas for executable evaluation of AI agents using deterministic feasibility checks.
Elecbench: a power dispatch evaluation benchmark for large language models
5 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
representative citing papers
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.
EngiBench shows LLMs accuracy drops with task complexity, degrades under perturbations, and stays below human performance on open-ended engineering problems.
An empirical study evaluating tool-augmented LLM agents on 243 real-world energy analytics problems across data retrieval, knowledge interpretation, and quantitative modeling using domain-specific tools and multi-dimensional scoring.
Hybrid pipeline using YOLO vision and ngspice verification raises circuit analysis accuracy from Gemini's 79.52% baseline to 97.59%, with similar gains on hand-drawn diagrams.
citing papers explorer
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Power Systems Agent Benchmark: Executable Evaluation of AI Agents in Electric Power Engineering
Introduces the Power Systems Agent Benchmark with 41 task families across eight power engineering areas for executable evaluation of AI agents using deterministic feasibility checks.
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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.
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EngiBench: A Benchmark for Evaluating Large Language Models on Engineering Problem Solving
EngiBench shows LLMs accuracy drops with task complexity, degrades under perturbations, and stays below human performance on open-ended engineering problems.
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How Do Tool-Augmented LLM Agents Perform on Real-World Energy Analytics Tasks?
An empirical study evaluating tool-augmented LLM agents on 243 real-world energy analytics problems across data retrieval, knowledge interpretation, and quantitative modeling using domain-specific tools and multi-dimensional scoring.
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Enhancing Large Language Model-Based Systems for End-to-End Circuit Analysis Problem Solving
Hybrid pipeline using YOLO vision and ngspice verification raises circuit analysis accuracy from Gemini's 79.52% baseline to 97.59%, with similar gains on hand-drawn diagrams.