LaMAGIC2: Advanced Circuit Formulations for Language Model-Based Analog Topology Generation

• URL: http://arxiv.org/abs/2506.10235v2
• Date: Sat, 26 Jul 2025 01:50:51 GMT
• Title: LaMAGIC2: Advanced Circuit Formulations for Language Model-Based Analog Topology Generation
• Authors: Chen-Chia Chang, Wan-Hsuan Lin, Yikang Shen, Yiran Chen, Xin Zhang,
• Abstract summary: We introduce LaMAGIC2, a succinct float-input canonical formulation with identifier for language model-based analog topology generation.<n>LaMAGIC2 achieves 34% higher success rates under a tight tolerance of 0.01 and 10X lower MSEs compared to a prior method.
• Score: 14.261506284722062
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Automation of analog topology design is crucial due to customized requirements of modern applications with heavily manual engineering efforts. The state-of-the-art work applies a sequence-to-sequence approach and supervised finetuning on language models to generate topologies given user specifications. However, its circuit formulation is inefficient due to O(|V |2) token length and suffers from low precision sensitivity to numeric inputs. In this work, we introduce LaMAGIC2, a succinct float-input canonical formulation with identifier (SFCI) for language model-based analog topology generation. SFCI addresses these challenges by improving component-type recognition through identifier-based representations, reducing token length complexity to O(|V |), and enhancing numeric precision sensitivity for better performance under tight tolerances. Our experiments demonstrate that LaMAGIC2 achieves 34% higher success rates under a tight tolerance of 0.01 and 10X lower MSEs compared to a prior method. LaMAGIC2 also exhibits better transferability for circuits with more vertices with up to 58.5% improvement. These advancements establish LaMAGIC2 as a robust framework for analog topology generation.

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