AnalogMaster applies large language models to end-to-end analog IC design automation, converting images to netlists and optimizing parameters to achieve 92.9% Pass@1 and 99.9% Pass@5 success on 15 test circuits using GPT-5.
LaMAGIC: Language-model-based topology generation for analog integrated cir- cuits
3 Pith papers cite this work, alongside 5 external citations. Polarity classification is still indexing.
3
Pith papers citing it
5
external citations · external index
years
2026 3verdicts
UNVERDICTED 3representative citing papers
ARCS generates valid SPICE-simulatable analog circuits in milliseconds via graph VAE, flow-matching, and GRPO reinforcement learning, reaching 99.9% validity with 8 evaluations across 32 topologies.
Survey of GenAI in PCB design lifecycle presenting taxonomy, technical challenges, and research directions.
citing papers explorer
-
AnalogMaster: Large Language Model-based Automated Analog IC Design Framework from Image to Layout
AnalogMaster applies large language models to end-to-end analog IC design automation, converting images to netlists and optimizing parameters to achieve 92.9% Pass@1 and 99.9% Pass@5 success on 15 test circuits using GPT-5.
-
ARCS: Autoregressive Circuit Synthesis with Topology-Aware Graph Attention and Spec Conditioning
ARCS generates valid SPICE-simulatable analog circuits in milliseconds via graph VAE, flow-matching, and GRPO reinforcement learning, reaching 99.9% validity with 8 evaluations across 32 topologies.
-
Surveying GenAI-based Automation in Printed Circuit Board Design and Test
Survey of GenAI in PCB design lifecycle presenting taxonomy, technical challenges, and research directions.