SPARC用多智能体系统结合物理仿真，让AI更准地解答电路图问题。
SPARC: A Multi-Agent System for Electrical Circuit Question Answering
- 用LLM生成可执行的物理仿真程序来推理电路
- 准确率达83%，比基线最高提升58个百分点
- 能自动诊断错误，适合需要可靠推理的工程场景
电路图问答任务需要复杂的数学推理，这对多模态大模型仍具挑战。我们提出SPARC，一种多智能体系统，通过基于可执行物理仿真的推理来回答电路图问题。SPARC利用大语言模型智能体生成、执行和分析仿真程序，从设计上提升了准确率与可靠性。实验显示其准确率达到83%，相较于基线模型最高有58%的绝对提升，同时支持系统的错误诊断。
原文摘要 · Abstract (English)
Electrical circuit diagram QA tasks require complex mathematical reasoning, which remains challenging for multimodal LLMs. We present SPARC, a multi-agent system that answers questions over circuit diagrams by grounding reasoning in executable physics-based simulations. SPARC uses LLM agents to synthesize, execute, and analyze simulation programs, improving accuracy and reliability by design. It achieves 83% accuracy, with up to a 58% absolute improvement over baselines, while enabling systematic error diagnosis.
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