mlsanityData to 7 Oct 2026

LayoutCopilot: An LLM-powered Multi-agent Collaborative Framework for Interactive Analog Layout Design

arXiv 2406.18873 ↗First posted 27 Jun 2024cs.ARcited by 24

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Abstract (arXiv)

Analog layout design heavily involves interactive processes between humans and design tools. Electronic Design Automation (EDA) tools for this task are usually designed to use scripting commands or visualized buttons for manipulation, especially for interactive automation functionalities, which have a steep learning curve and cumbersome user experience, making a notable barrier to designers' adoption. Aiming to address such a usability issue, this paper introduces LayoutCopilot, a pioneering multi-agent collaborative framework powered by Large Language Models (LLMs) for interactive analog layout design. LayoutCopilot simplifies human-tool interaction by converting natural language instructions into executable script commands, and it interprets high-level design intents into actionable suggestions, significantly streamlining the design process. Experimental results demonstrate the flexibility, efficiency, and accessibility of LayoutCopilot in handling real-world analog designs.

Key facts. Cited by 24 papers in the map (data through 7 Oct 2026). First posted on arXiv 27 Jun 2024.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 3; 2025: 11; 2026: 10.

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  1. 2025A Survey of Research in Large Language Models for Electronic Design Automationcited by 38
  2. 2024LEDRO: LLM-Enhanced Design Space Reduction and Optimization for Analog Circuitscited by 22
  3. 2024SPICEPilot: Navigating SPICE Code Generation and Simulation with AI Guidancecited by 10
  4. 2025AMSnet 2.0: A Large AMS Database with AI Segmentation for Net Detectioncited by 9
  5. 2025MenTeR: A fully-automated Multi-agenT workflow for end-to-end RF/Analog Circuits Netlist Designcited by 6
  6. 2025FALCON: An ML Framework for Fully Automated Layout-Constrained Analog Circuit Designcited by 4
  7. 2025Bias in the Loop: How Humans Evaluate AI-Generated Suggestionscited by 4
  8. 2025Large Language Models (LLMs) for Electronic Design Automation (EDA)cited by 3
  9. 2025Timing Analysis Agent: Autonomous Multi-Corner Multi-Mode (MCMM) Timing Debugging with Timing Debug Relation Graphcited by 2
  10. 2025SANGAM: SystemVerilog Assertion Generation via Monte Carlo Tree Self-Refinecited by 2
  11. 2025AgenticTCAD: A LLM-based Multi-Agent Framework for Automated TCAD Code Generation and Device Optimizationcited by 2
  12. 2026PANDA: An LLM-Enhanced Performance-Driven Analog Design Framework Bridging Design Intent and Layout Generationcited by 2
12 more
  1. 2024CktGen: Automated Analog Circuit Design with Generative Artificial Intelligencecited by 1
  2. 2025Dataset Construction for Training LLM to Learn Analog Circuit Knowledgecited by 1
  3. 2026Can an Actor-Critic Optimization Framework Improve Analog Design?cited by 1
  4. 2026Foundation-Model-Based Agents in Industrial Automation: Purposes, Capabilities, and Open Challengescited by 1
  5. 2026AgenticECO: An Agentic Framework for ECO on 3D Integrated Circuitscited by 1
  6. 2026ZhuLong: Execution-Grounded LLM Agent for EDA Scripting with Offline API Self-Explorationcited by 1
  7. 2025PCEval: A Benchmark for Evaluating Physical Computing Capabilities of Large Language Modelscited by 0
  8. 2026EM-Aware Physical Synthesis: Neural Inductor Modeling and Intelligent Placement & Routing for RF Circuitscited by 0
  9. 2026Surveying GenAI-based Automation in Printed Circuit Board Design and Testcited by 0
  10. 2026Agentic Electronic Design Automation: A Handoff Perspectivecited by 0
  11. 2026Simulation-Aware In-Context Policy Improvement for LLM-Aided Analog Layout Refinementcited by 0
  12. 2026PICasso: An AI-Enabled Design Framework for Autonomous Optimization of Silicon Photonic Devicescited by 0