# AMSnet-KG: A Netlist Dataset for LLM-based AMS Circuit Auto-Design Using Knowledge Graph RAG

arXiv: https://arxiv.org/abs/2411.13560 · HTML: https://mlsanity.com/paper/2411.13560/

## Key facts

- Cited by 16 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 49 references that are in the map.
- First posted on arXiv 7 Nov 2024.

## Builds on (most cited first, 12 of 12)

- [Chain-of-Thought Prompting Elicits Reasoning in Large Language Models](https://mlsanity.com/paper/2201.11903/) (2022)
- [You Only Look Once: Unified, Real-Time Object Detection](https://mlsanity.com/paper/1506.02640/) (2015)
- [Optuna: A Next-generation Hyperparameter Optimization Framework](https://mlsanity.com/paper/1907.10902/) (2019)
- [What Makes Good In-Context Examples for GPT-3?](https://mlsanity.com/paper/2101.06804/) (2021)
- [VeriGen: A Large Language Model for Verilog Code Generation](https://mlsanity.com/paper/2308.00708/) (2023)
- [Benchmarking Large Language Models for Automated Verilog RTL Code Generation](https://mlsanity.com/paper/2212.11140/) (2022)
- [GCN-RL Circuit Designer: Transferable Transistor Sizing with Graph Neural Networks and Reinforcement Learning](https://mlsanity.com/paper/2005.00406/) (2020)
- [CktGNN: Circuit Graph Neural Network for Electronic Design Automation](https://mlsanity.com/paper/2308.16406/) (2023)
- [LLM4EDA: Emerging Progress in Large Language Models for Electronic Design Automation](https://mlsanity.com/paper/2401.12224/) (2023)
- [AMSNet: Netlist Dataset for AMS Circuits](https://mlsanity.com/paper/2405.09045/) (2024)
- [AICircuit: A Multi-Level Dataset and Benchmark for AI-Driven Analog Integrated Circuit Design](https://mlsanity.com/paper/2407.18272/) (2024)
- [FUBOCO: Structure Synthesis of Basic Op-Amps by FUnctional BlOck COmposition](https://mlsanity.com/paper/2101.07517/) (2021)

## Built on by (most cited first, 16 of 16)

- [AMSbench: A Comprehensive Benchmark for Evaluating MLLM Capabilities in AMS Circuits](https://mlsanity.com/paper/2505.24138/) (2025)
- [AMSnet 2.0: A Large AMS Database with AI Segmentation for Net Detection](https://mlsanity.com/paper/2505.09155/) (2025)
- [MenTeR: A fully-automated Multi-agenT workflow for end-to-end RF/Analog Circuits Netlist Design](https://mlsanity.com/paper/2505.22990/) (2025)
- [AnalogAgent: Self-Improving Analog Circuit Design Automation with LLM Agents](https://mlsanity.com/paper/2603.23910/) (2026)
- [Evaluating LLM-based Workflows for Switched-Mode Power Supply Design](https://mlsanity.com/paper/2507.10639/) (2025)
- [Dataset Construction for Training LLM to Learn Analog Circuit Knowledge](https://mlsanity.com/paper/2508.10409/) (2025)
- [SABLE: An NDA-Safe Closed-Loop LLM Framework for Analog Circuit Optimization in Industrial EDA Flows](https://mlsanity.com/paper/2607.03701/) (2026)
- [RF-Agent: A Practical Framework for Building Language Agents for RFIC Design](https://mlsanity.com/paper/2607.18772/) (2026)
- [AMSnet-q: Unsupervised Circuit Identification and Performance Labeling for AMS Circuits](https://mlsanity.com/paper/2605.01404/) (2026)
- [Surveying GenAI-based Automation in Printed Circuit Board Design and Test](https://mlsanity.com/paper/2606.17074/) (2026)
- [AutoVSR: Automatic Visual-to-Symbolic Reasoning for Symbolic Expression Generation from Circuit Schematic](https://mlsanity.com/paper/2607.11338/) (2026)
- [EXPLORE: Exploration with Guided Search for Analog Topology Generation using Language Models](https://mlsanity.com/paper/2607.13416/) (2026)
- [AaLLM: An End-to-End Analog Circuit Design Framework from Topology Generation to Sizing Using Large Language Models](https://mlsanity.com/paper/2608.13472/) (2026)
- [PCBnet: A Dataset and Automatic Construction of SPICE Netlists from Schematic Images](https://mlsanity.com/paper/2608.27923/) (2026)
- [Circuit-MLLM: Topological Logic-Guided Latent-Space Visual Reasoning for Circuit Schematic Understanding](https://mlsanity.com/paper/2609.15668/) (2026)
- [Long-Horizon Analog Design Bench: Benchmarking Agents on Hours-Long Analog and Mixed-Signal Circuit Design Tasks](https://mlsanity.com/paper/2609.33356/) (2026)

## Abstract (arXiv)

High-performance analog and mixed-signal (AMS) circuits are mainly full-custom designed, which is time-consuming and labor-intensive. A significant portion of the effort is experience-driven, which makes the automation of AMS circuit design a formidable challenge. Large language models (LLMs) have emerged as powerful tools for Electronic Design Automation (EDA) applications, fostering advancements in the automatic design process for large-scale AMS circuits. However, the absence of high-quality datasets has led to issues such as model hallucination, which undermines the robustness of automatically generated circuit designs. To address this issue, this paper introduces AMSnet-KG, a dataset encompassing various AMS circuit schematics and netlists. We construct a knowledge graph with annotations on detailed functional and performance characteristics. Facilitated by AMSnet-KG, we propose an automated AMS circuit generation framework that utilizes the comprehensive knowledge embedded in LLMs. We first formulate a design strategy (e.g., circuit architecture using a number of circuit components) based on required specifications. Next, matched circuit components are retrieved and assembled into a complete topology, and transistor sizing is obtained through Bayesian optimization. Simulation results of the netlist are fed back to the LLM for further topology refinement, ensuring the circuit design specifications are met. We perform case studies of operational amplifier and comparator design to verify the automatic design flow from specifications to netlists with minimal human effort. The dataset used in this paper will be open-sourced upon publishing of this paper.