AI RESEARCH

CircuitFormer: A Circuit Language Model for Analog Topology Design from Natural Language Prompt

arXiv CS.AI

ArXi:2605.05773v1 Announce Type: new Automating analog circuit design remains a longstanding challenge in Electronic Design Automation (EDA). While Transformer-based Large Language Models (LLMs) have revolutionized software code generation, their application to analog hardware design is hindered by two critical limitations: (i) the scarcity of analog design datasets containing natural language description of a design and its corresponding netlist, and (ii) the inefficiency of general-purpose tokenizers (e.g., Byte Pair Encoding (BPE)) in capturing the inherent graph structure of circuits.