<ul data-eligibleForWebStory="true"><li>LaMAGIC2 introduces a float-input canonical formulation for language model-based analog topology generation.</li><li>Existing approaches suffer inefficiencies and low precision sensitivity to numeric inputs.</li><li>LaMAGIC2 aims to improve component-type recognition, reduce token length complexity, and enhance numeric precision sensitivity.</li><li>Experiments show that LaMAGIC2 outperforms previous methods with 34% higher success rates under tight tolerances and 10X lower MSEs.</li><li>It also demonstrates improved transferability for circuits with more vertices, up to 58.5% improvement.</li><li>The advancements in LaMAGIC2 establish it as a robust framework for analog topology generation.</li></ul>

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

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