mlsanityData to 14 Oct 2026

LEDRO: LLM-Enhanced Design Space Reduction and Optimization for Analog Circuits

arXiv 2411.12930 ↗First posted 19 Nov 2024cs.LG cs.SY eess.SYcited by 22

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Abstract (arXiv)

Traditional approaches for designing analog circuits are time-consuming and require significant human expertise. Existing automation efforts using methods like Bayesian Optimization (BO) and Reinforcement Learning (RL) are sub-optimal and costly to generalize across different topologies and technology nodes. In our work, we introduce a novel approach, LEDRO, utilizing Large Language Models (LLMs) in conjunction with optimization techniques to iteratively refine the design space for analog circuit sizing. LEDRO is highly generalizable compared to other RL and BO baselines, eliminating the need for design annotation or model training for different topologies or technology nodes. We conduct a comprehensive evaluation of our proposed framework and baseline on 22 different Op-Amp topologies across four FinFET technology nodes. Results demonstrate the superior performance of LEDRO as it outperforms our best baseline by an average of 13% FoM improvement with 2.15x speed-up on low complexity Op-Amps and 48% FoM improvement with 1.7x speed-up on high complexity Op-Amps. This highlights LEDRO's effective performance, efficiency, and generalizability.

Key facts. Cited by 22 papers in the map (data through 14 Oct 2026). Builds on 11 of its 27 references that are in the map. First posted on arXiv 19 Nov 2024.

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11 of 27 references.

References · 11

  1. 2024The Llama 3 Herd of Modelscited by 14,715
  2. 2023Reflexion: Language Agents with Verbal Reinforcement Learningcited by 4,276
  3. 2019Scalable Global Optimization via Local Bayesian Optimizationcited by 374
  4. 2020GCN-RL Circuit Designer: Transferable Transistor Sizing with Graph Neural Networks and Reinforcement Learningcited by 89
  5. 2024AnalogCoder: Analog Circuit Design via Training-Free Code Generationcited by 84
  6. 2020AutoCkt: Deep Reinforcement Learning of Analog Circuit Designscited by 51
  7. 2024ADO-LLM: Analog Design Bayesian Optimization with In-Context Learning of Large Language Modelscited by 44
  8. 2024AmpAgent: An LLM-based Multi-Agent System for Multi-stage Amplifier Schematic Design from Literature for Process and Performance Portingcited by 29
  9. 2024LayoutCopilot: An LLM-powered Multi-agent Collaborative Framework for Interactive Analog Layout Designcited by 25
  10. 2021DNN-Opt: An RL Inspired Optimization for Analog Circuit Sizing using Deep Neural Networkscited by 18
  11. 2024LLM-Enhanced Bayesian Optimization for Efficient Analog Layout Constraint Generationcited by 13

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 8; 2026: 14.

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  1. 2025AnalogCoder-Pro: Unifying Analog Circuit Generation and Optimization via Multi-modal LLMscited by 15
  2. 2025EEsizer: LLM-Based AI Agent for Sizing of Analog and Mixed Signal Circuitcited by 13
  3. 2025iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMscited by 7
  4. 2025TopoSizing: An LLM-aided Framework of Topology-based Understanding and Sizing for AMS Circuitscited by 7
  5. 2025LLM-based AI Agent for Sizing of Analog and Mixed Signal Circuitcited by 6
  6. 2025HeaRT: A Hierarchical Circuit Reasoning Tree-Based Agentic Framework for AMS Design Optimizationcited by 5
  7. 2026AutoSizer: Automatic Sizing of Analog and Mixed-Signal Circuits via Large Language Model (LLM) Agentscited by 5
  8. 2025Evaluating LLM-based Workflows for Switched-Mode Power Supply Designcited by 2
  9. 2025Dataset Construction for Training LLM to Learn Analog Circuit Knowledgecited by 1
  10. 2026Can an Actor-Critic Optimization Framework Improve Analog Design?cited by 1
  11. 2026SABLE: An NDA-Safe Closed-Loop LLM Framework for Analog Circuit Optimization in Industrial EDA Flowscited by 1
  12. 2026RF-Agent: A Practical Framework for Building Language Agents for RFIC Designcited by 1
10 more
  1. 2026VLM-CAD: VLM-Optimized Collaborative Agent Design Workflow for Analog Circuit Sizingcited by 0
  2. 2026LLM-Assisted Op-Amp Behavioral-Level Design via Agentic Human-Mimicking Reasoningcited by 0
  3. 2026A Self-Calibrating Framework for Analog Circuit Sizing Using LLM-Derived Analytical Equationscited by 0
  4. 2026Agentic Electronic Design Automation: A Handoff Perspectivecited by 0
  5. 2026AutoVSR: Automatic Visual-to-Symbolic Reasoning for Symbolic Expression Generation from Circuit Schematiccited by 0
  6. 2026Towards Reliable AI-Assisted Analog Design: Template-Constrained LLM Agents for SAR ADC Generationcited by 0
  7. 2026AaLLM: An End-to-End Analog Circuit Design Framework from Topology Generation to Sizing Using Large Language Modelscited by 0
  8. 2026Simulation-Aware In-Context Policy Improvement for LLM-Aided Analog Layout Refinementcited by 0
  9. 2026AgenticSizing: A Large Language Model-based Multi-Agent Framework for Analog Circuit Sizingcited by 0
  10. 2026Long-Horizon Analog Design Bench: Benchmarking Agents on Hours-Long Analog and Mixed-Signal Circuit Design Taskscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025LLM-USO: Large Language Model-based Universal Sizing Optimizer
  2. 2025EasySize: Elastic Analog Circuit Sizing via LLM-Guided Heuristic Search
  3. 2024AnalogXpert: Automating Analog Topology Synthesis by Incorporating Circuit Design Expertise into Large Language Models
  4. 2026OSIRIS: Bridging Analog Circuit Design and Machine Learning with Scalable Dataset Generation
  5. 2025A Large Language Model-based Multi-Agent Framework for Analog Circuits' Sizing Relationships Extraction
  6. 2024INSIGHT: Universal Neural Simulator for Analog Circuits Harnessing Autoregressive Transformers
  7. 2025CIRCUIT: A Benchmark for Circuit Interpretation and Reasoning Capabilities of LLMs
  8. 2025AUTOCIRCUIT-RL: Reinforcement Learning-Driven LLM for Automated Circuit Topology Generation