30 citations · 74 across the 13 of their papers we have counts for
6 papers · 1 filter
When Forgetting Builds Reliability: LLM Unlearning for Reliable Hardware Code Generation
Yiwen Liang, Qiufeng Li, Shikai Wang +1
Large Language Models (LLMs) have shown strong potential in accelerating digital hardware design through automated code generation. Yet, ensuring their reliability remains a critic…
AnalogGenie: A Generative Engine for Automatic Discovery of Analog Circuit Topologies
Jian Gao, Weidong Cao, Junyi Yang +1
The massive and large-scale design of foundational semiconductor integrated circuits (ICs) is crucial to sustaining the advancement of many emerging and future technologies, such a…
CktGNN: Circuit Graph Neural Network for Electronic Design Automation
Zehao Dong, Weidong Cao, Muhan Zhang +3
The electronic design automation of analog circuits has been a longstanding challenge in the integrated circuit field due to the huge design space and complex design trade-offs amo…
Domain Knowledge-Infused Deep Learning for Automated Analog/Radio-Frequency Circuit Parameter Optimization
Weidong Cao, Mouhacine Benosman, Xuan Zhang +1
The design automation of analog circuits is a longstanding challenge. This paper presents a reinforcement learning method enhanced by graph learning to automate the analog circuit…
Domain Knowledge-Based Automated Analog Circuit Design with Deep Reinforcement Learning
Weidong Cao, Mouhacine Benosman, Xuan Zhang +1
The design automation of analog circuits is a longstanding challenge in the integrated circuit field. This paper presents a deep reinforcement learning method to expedite the desig…
Neural Network-Inspired Analog-to-Digital Conversion to Achieve Super-Resolution with Low-Precision RRAM Devices
Weidong Cao, Liu Ke, Ayan Chakrabarti +1
Recent works propose neural network- (NN-) inspired analog-to-digital converters (NNADCs) and demonstrate their great potentials in many emerging applications. These NNADCs often r…