AI RESEARCH
ChipLingo: A Systematic Training Framework for Large Language Models in EDA
arXiv CS.LG
•
ArXi:2604.27415v1 Announce Type: new With the rapid advancement of semiconductor technology, Electronic Design Automation (EDA) has become an increasingly knowledge-intensive and document-driven engineering domain. Although large language models (LLMs) have shown strong general capabilities, applying them directly to EDA remains challenging due to limited domain expertise, cross-tool knowledge confusion, and degraded retrieval-augmented generation (RAG) performance after domain.