activity
20232026
most citedA Survey of Research in Large Language Models for Electronic Design Automation

3 citations · 6 across the 9 of their papers we have counts for

collaborators

10 papers

cs.AR2026

DiffPower: GPU-Accelerated Differentiable Switching Power Analysis and Optimization

Isaac Jacobson, Zheng Zhao, Rashmi Mehrotra +3

Accurate and scalable switching power analysis remains a critical bottleneck in modern physical design, often forcing a trade-off between computational speed and modeling fidelity.…

cs.CV2026

SCALE: Self-Supervised Constraint-Aware Layout GEneration for Local P&R DRV Fixing at Advanced Nodes

Chia-Tung Ho, Haoyu Yang, Guanglei Zhou +6

As semiconductor manufacturing advances toward sub-2nm nodes, local place-and-route (P&R) design-rule violation (DRV) fixing is increasingly limited by complex rule interactions, d…

cs.LG2026

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

Guanglei Zhou, Chen-Chia Chang, Yikang Shen +5

Automating analog circuit topology design is essential to reduce the extensive manual effort required to meet increasingly diverse and customized application demands. Recent advanc…

cs.LG2025

CROP: Circuit Retrieval and Optimization with Parameter Guidance using LLMs

Jingyu Pan, Isaac Jacobson, Zheng Zhao +5

Modern very large-scale integration (VLSI) design requires the implementation of integrated circuits using electronic design automation (EDA) tools. Due to the complexity of EDA al…

cs.AI2025

AutoEDA: Enabling EDA Flow Automation through Microservice-Based LLM Agents

Yiyi Lu, Hoi Ian Au, Junyao Zhang +8

Electronic Design Automation (EDA) remains heavily reliant on tool command language (Tcl) scripting to drive complex RTL-to-GDSII flows. This scripting-based paradigm is labor-inte…

cs.LG2025★ 3 cited

A Survey of Research in Large Language Models for Electronic Design Automation

Jingyu Pan, Guanglei Zhou, Chen-Chia Chang +3

Within the rapidly evolving domain of Electronic Design Automation (EDA), Large Language Models (LLMs) have emerged as transformative technologies, offering unprecedented capabilit…

quant-ph2024

qGDP: Quantum Legalization and Detailed Placement for Superconducting Quantum Computers

Junyao Zhang, Guanglei Zhou, Feng Cheng +6

Noisy Intermediate-Scale Quantum (NISQ) computers are currently limited by their qubit numbers, which hampers progress towards fault-tolerant quantum computing. A major challenge i…

cs.AR2024★ 3 cited

A Survey: Collaborative Hardware and Software Design in the Era of Large Language Models

Cong Guo, Feng Cheng, Zhixu Du +21

The rapid development of large language models (LLMs) has significantly transformed the field of artificial intelligence, demonstrating remarkable capabilities in natural language…

cs.CV2024

PatternPaint: Practical Layout Pattern Generation Using Diffusion-Based Inpainting

Guanglei Zhou, Bhargav Korrapati, Gaurav Rajavendra Reddy +5

Generating diverse VLSI layout patterns is essential for various downstream tasks in design for manufacturing, as design rules continually evolve during the development of new tech…

cs.LG2023

PANDA: Architecture-Level Power Evaluation by Unifying Analytical and Machine Learning Solutions

Qijun Zhang, Shiyu Li, Guanglei Zhou +4

Power efficiency is a critical design objective in modern microprocessor design. To evaluate the impact of architectural-level design decisions, an accurate yet efficient architect…