mlsanityData to 7 Oct 2026

LaMAGIC: Language-Model-based Topology Generation for Analog Integrated Circuits

arXiv 2407.18269 ↗First posted 19 Jul 2024cs.AR cs.AI cs.LGcited by 32

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Abstract (arXiv)

In the realm of electronic and electrical engineering, automation of analog circuit is increasingly vital given the complexity and customized requirements of modern applications. However, existing methods only develop search-based algorithms that require many simulation iterations to design a custom circuit topology, which is usually a time-consuming process. To this end, we introduce LaMAGIC, a pioneering language model-based topology generation model that leverages supervised finetuning for automated analog circuit design. LaMAGIC can efficiently generate an optimized circuit design from the custom specification in a single pass. Our approach involves a meticulous development and analysis of various input and output formulations for circuit. These formulations can ensure canonical representations of circuits and align with the autoregressive nature of LMs to effectively addressing the challenges of representing analog circuits as graphs. The experimental results show that LaMAGIC achieves a success rate of up to 96% under a strict tolerance of 0.01. We also examine the scalability and adaptability of LaMAGIC, specifically testing its performance on more complex circuits. Our findings reveal the enhanced effectiveness of our adjacency matrix-based circuit formulation with floating-point input, suggesting its suitability for handling intricate circuit designs. This research not only demonstrates the potential of language models in graph generation, but also builds a foundational framework for future explorations in automated analog circuit design.

Key facts. Cited by 32 papers in the map (data through 7 Oct 2026). Builds on 5 of its 13 references that are in the map. First posted on arXiv 19 Jul 2024.

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5 of 13 references.

References · 5

  1. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  2. 2022Scaling Instruction-Finetuned Language Modelscited by 2,997
  3. 2021Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processingcited by 2,222
  4. 2022CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesiscited by 876
  5. 2023CodeGen2: Lessons for Training LLMs on Programming and Natural Languagescited by 124

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 3; 2025: 14; 2026: 15.

32 papers.

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  1. 2025AnalogGenie: A Generative Engine for Automatic Discovery of Analog Circuit Topologiescited by 35
  2. 2024AnalogXpert: Automating Analog Topology Synthesis by Incorporating Circuit Design Expertise into Large Language Modelscited by 17
  3. 2025AnalogCoder-Pro: Unifying Analog Circuit Generation and Optimization via Multi-modal LLMscited by 14
  4. 2024Schemato -- An LLM for Netlist-to-Schematic Conversioncited by 11
  5. 2025AUTOCIRCUIT-RL: Reinforcement Learning-Driven LLM for Automated Circuit Topology Generationcited by 10
  6. 2025AMSnet 2.0: A Large AMS Database with AI Segmentation for Net Detectioncited by 9
  7. 2025MuaLLM: A Multimodal Large Language Model Agent for Circuit Design Assistance with Hybrid Contextual Retrieval-Augmented Generationcited by 8
  8. 2025LLM-DSE: Searching Accelerator Parameters with LLM Agentscited by 7
  9. 2025LaMAGIC2: Advanced Circuit Formulations for Language Model-Based Analog Topology Generationcited by 6
  10. 2025FALCON: An ML Framework for Fully Automated Layout-Constrained Analog Circuit Designcited by 4
  11. 2025A Large Language Model-based Multi-Agent Framework for Analog Circuits' Sizing Relationships Extractioncited by 3
  12. 2025CircuitSense: A Hierarchical MLLM Benchmark Bridging Visual Comprehension and Symbolic Reasoning in Engineering Design Processcited by 3
20 more
  1. 2025ZeroSim: Zero-Shot Analog Circuit Evaluation with Unified Transformer Embeddingscited by 2
  2. 2026OSIRIS: Bridging Analog Circuit Design and Machine Learning with Scalable Dataset Generationcited by 2
  3. 2026CircuitFormer: A Circuit Language Model for Analog Topology Design from Natural Language Promptcited by 2
  4. 2024CktGen: Automated Analog Circuit Design with Generative Artificial Intelligencecited by 1
  5. 2026PowerGenie: Analytically-Guided Evolutionary Discovery of Superior Reconfigurable Power Converterscited by 1
  6. 2026AstRL: Analog and Mixed-Signal Circuit Synthesis with Deep Reinforcement Learningcited by 1
  7. 2026AnalogRetriever: Learning Cross-Modal Representations for Analog Circuit Retrievalcited by 1
  8. 2026RF-Agent: A Practical Framework for Building Language Agents for RFIC Designcited by 1
  9. 2025PrefixAgent: An LLM-Powered Design Framework for Efficient Prefix Adder Optimizationcited by 0
  10. 2025AnalogFed: Privacy-Preserving Discovery of Analog Circuits at Scale with Federated Generative AIcited by 0
  11. 2025SynCircuit: Automated Generation of New Synthetic RTL Circuits Can Enable Big Data in Circuitscited by 0
  12. 2026EM-Aware Physical Synthesis: Neural Inductor Modeling and Intelligent Placement & Routing for RF Circuitscited by 0
  13. 2026Neural Proposals, Symbolic Guarantees: Neuro-Symbolic Graph Generative Modelingcited by 0
  14. 2026ARCS: Autoregressive Circuit Synthesis with Topology-Aware Graph Attention and Spec Conditioningcited by 0
  15. 2026SchGen: PCB Schematic Generation with Semantic-Grounded Code Representationscited by 0
  16. 2026Towards Reliable AI-Assisted Analog Design: Template-Constrained LLM Agents for SAR ADC Generationcited by 0
  17. 2026AaLLM: An End-to-End Analog Circuit Design Framework from Topology Generation to Sizing Using Large Language Modelscited by 0
  18. 2026Long-Horizon Analog Design Bench: Benchmarking Agents on Hours-Long Analog and Mixed-Signal Circuit Design Taskscited by 0
  19. 2026Inspector: Conversational and Lightweight Analyzer of Analog Circuit Layouts Using LLM and CNNscited by 0
  20. 2026cktFormer: Transformer-Based Approach for Automated Analog Circuit Designcited by 0