CIRCUITSYNTH: Leveraging Large Language Models for Circuit Topology Synthesis
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Abstract (arXiv)
Circuit topology generation plays a crucial role in the design of electronic circuits, influencing the fundamental functionality of the circuit. In this paper, we introduce CIRCUITSYNTH, a novel approach that harnesses LLMs to facilitate the automated synthesis of valid circuit topologies. With a dataset comprising both valid and invalid circuit configurations, CIRCUITSYNTH employs a sophisticated two-phase methodology, comprising Circuit Topology Generation and Circuit Topology Refinement. Experimental results demonstrate the effectiveness of CIRCUITSYNTH compared to various fine-tuned LLM variants. Our approach lays the foundation for future research aimed at enhancing circuit efficiency and specifying output voltage, thus enabling the automated generation of circuit topologies with improved performance and adherence to design requirements.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 9 of its 15 references that are in the map. First posted on arXiv 6 Jun 2024.
Builds on
9 of 15 references.
References · 9
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Citing papers per year: 2025: 2; 2026: 3.
5 papers.
- 2025AUTOCIRCUIT-RL: Reinforcement Learning-Driven LLM for Automated Circuit Topology Generationcited by 10
- 2025MuaLLM: A Multimodal Large Language Model Agent for Circuit Design Assistance with Hybrid Contextual Retrieval-Augmented Generationcited by 8
- 2026SABLE: An NDA-Safe Closed-Loop LLM Framework for Analog Circuit Optimization in Industrial EDA Flowscited by 1
- 2026ARCS: Autoregressive Circuit Synthesis with Topology-Aware Graph Attention and Spec Conditioningcited by 0
- 2026Surveying GenAI-based Automation in Printed Circuit Board Design and Testcited by 0
- 2026SABLE: An NDA-Safe Closed-Loop LLM Framework for Analog Circuit Optimization in Industrial EDA Flows4 Jul 2026
- 2026Surveying GenAI-based Automation in Printed Circuit Board Design and Test10 Jun 2026
- 2026ARCS: Autoregressive Circuit Synthesis with Topology-Aware Graph Attention and Spec Conditioning30 Mar 2026
- 2025MuaLLM: A Multimodal Large Language Model Agent for Circuit Design Assistance with Hybrid Contextual Retrieval-Augmented Generation11 Aug 2025
- 2025AUTOCIRCUIT-RL: Reinforcement Learning-Driven LLM for Automated Circuit Topology Generation3 Jun 2025