New Interaction Paradigm for Complex EDA Software Leveraging GPT
Not on the map. Why?
Abstract (arXiv)
Electronic Design Automation (EDA) tools such as KiCad offer powerful functionalities but remain difficult to use, particularly for beginners, due to their steep learning curves and fragmented documentation. To address this challenge, we present SmartonAI, an AI-assisted interaction system that integrates large language models into the EDA workflow, enabling natural language communication, intelligent task decomposition, and contextual plugin execution. SmartonAI consists of two main components: a Chat Plugin that breaks down user instructions into subtasks and retrieves tailored documentation, and a OneCommandLine Plugin that recommends and executes relevant plugins based on user intent. The system supports multilingual interaction and adapts to user feedback through incremental learning. Preliminary results suggest that SmartonAI significantly reduces onboarding time and enhances productivity, representing a promising step toward generalizable AI-assisted interaction paradigms for complex software systems.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 11 of its 29 references that are in the map. First posted on arXiv 27 Jul 2023.
Builds on
11 of 29 references.
References · 11
- 2017Attention Is All You Needcited by 60,361
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
- 2020Language Models are Few-Shot Learnerscited by 32,419
- 2023GPT-4 Technical Reportcited by 18,396
- 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,297
- 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,695
- 2021Evaluating Large Language Models Trained on Codecited by 8,320
- 2023Toolformer: Language Models Can Teach Themselves to Use Toolscited by 4,182
- 2020REALM: Retrieval-Augmented Language Model Pre-Trainingcited by 2,141
- 2023HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Facecited by 1,190
- 2023Using an LLM to Help With Code Understandingcited by 228
Built on by
Citing papers per year: 2023: 1; 2024: 2; 2025: 1.
4 papers.
- 2024AnalogCoder: Analog Circuit Design via Training-Free Code Generationcited by 84
- 2023LLM4EDA: Emerging Progress in Large Language Models for Electronic Design Automationcited by 40
- 2024LLMs and the Future of Chip Design: Unveiling Security Risks and Building Trustcited by 20
- 2025SecFSM: Knowledge Graph-Guided Verilog Code Generation for Secure Finite State Machines in Systems-on-Chipcited by 2
- 2025SecFSM: Knowledge Graph-Guided Verilog Code Generation for Secure Finite State Machines in Systems-on-Chip18 Aug 2025
- 2024AnalogCoder: Analog Circuit Design via Training-Free Code Generation23 May 2024
- 2024LLMs and the Future of Chip Design: Unveiling Security Risks and Building Trust11 May 2024
- 2023LLM4EDA: Emerging Progress in Large Language Models for Electronic Design Automation28 Dec 2023