arXiv AI June 16, 2026 By Haoyi Zhang, Weijian Fan, Xiaohan Gao, Bingyang Liu, Runsheng Wang, Yibo Lin

PANDA: An LLM-Enhanced Performance-Driven Analog Design Framework Bridging Design Intent and Layout Generation

arXiv:2606. 15052v1 Announce Type: cross Abstract: Traditional design of analog circuits heavily relies on manual interventions across topology, sizing, and layout, with prior automation addressing stages in isolation.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

llms

arXiv AI

2d ago

Simulation-Aware In-Context Policy Improvement for LLM-Aided Analog Layout Refinement

arXiv:2608. 13767v1 Announce Type: new Abstract: Analog IC layout design remains a labor-intensive iterative process dominated by simulation-driven refinement.

By Bingyang Liu, Ziming Wei, Xiaohan Gao, David Z. Pan

llms agents

arXiv Machine Learning

Jul 16

EXPLORE: Exploration with Guided Search for Analog Topology Generation using Language Models

arXiv:2607. 13416v1 Announce Type: new Abstract: Automating analog circuit topology design is essential to reduce the extensive manual effort required to meet increasingly diverse and customized application demands.

By Guanglei Zhou, Chen-Chia Chang, Yikang Shen, Jonathan Ku, Isaac Jacobson, Jingyu Pan, Yiran Chen, Xin Zhang

llms fine-tuning benchmarks

arXiv AI

5d ago

AaLLM: An End-to-End Analog Circuit Design Framework from Topology Generation to Sizing Using Large Language Models

arXiv:2608. 13472v1 Announce Type: cross Abstract: Analog circuit design is a time-consuming, iterative process in a nonlinear and high-dimensional design space that relies heavily on expert intuition.

By Mohammed Ayman Habib, Rylan Hart, Morteza Fayazi

llms rag agents benchmarks safety

arXiv AI

Jul 17

Towards Reliable AI-Assisted Analog Design: Template-Constrained LLM Agents for SAR ADC Generation

arXiv:2607. 14165v1 Announce Type: cross Abstract: While Large Language Models (LLMs) have demonstrated significant capability in software code generation, their application to analog Electronic Design Automation (EDA) is bottlenecked.

By Dimple Vijay Kochar, Hae-Seung Lee, Anantha P. Chandrakasan

llms agents multimodal safety

arXiv AI

1d ago

ATLAS: Scaffold-Free Algorithm Synthesis by LLMs via Embedding-Guided Quality-Diversity Search

arXiv:2608. 15546v1 Announce Type: new Abstract: Most LLM-based automated algorithm design methods optimize a designated component within a human-specified scaffold, fixing overall organization and component interactions.

By Danial Yazdani, Mohammad Nabi Omidvar, Yuan Sun, Maksud Ibrahimov, Xiaodong Li

llms rag benchmarks

arXiv AI

Jun 2

pcbGPT: Automatic PCB Schematic Synthesis from Natural Language Requirements

arXiv:2606. 01188v1 Announce Type: cross Abstract: Translating natural-language hardware requirements into correct printed circuit board (PCB) schematics remains difficult in embedded, IoT, and wearable development.

By Tobias King, Steven Kehrberg, Michael Beigl, Tobias R\"oddiger

Related stories

Simulation-Aware In-Context Policy Improvement for LLM-Aided Analog Layout Refinement

EXPLORE: Exploration with Guided Search for Analog Topology Generation using Language Models

AaLLM: An End-to-End Analog Circuit Design Framework from Topology Generation to Sizing Using Large Language Models

Towards Reliable AI-Assisted Analog Design: Template-Constrained LLM Agents for SAR ADC Generation

ATLAS: Scaffold-Free Algorithm Synthesis by LLMs via Embedding-Guided Quality-Diversity Search

pcbGPT: Automatic PCB Schematic Synthesis from Natural Language Requirements