21 citations · 22 across the 14 of their papers we have counts for
9 papers · 1 filter
DynamicRTL: RTL Representation Learning for Dynamic Circuit Behavior
Ruiyang Ma, Yunhao Zhou, Yipeng Wang +9
There is a growing body of work on using Graph Neural Networks (GNNs) to learn representations of circuits, focusing primarily on their static characteristics. However, these model…
Alignment Unlocks Complementarity: A Framework for Multiview Circuit Representation Learning
Zhengyuan Shi, Jingxin Wang, Wentao Jiang +5
Multiview learning on Boolean circuits holds immense promise, as different graph-based representations offer complementary structural and semantic information. However, the vast st…
TRACE: Learning to Compute on Circuit Graphs
Ziyang Zheng, Jiaying Zhu, Jingyi Zhou +1
Learning to compute, the ability to model the functional behavior of a circuit graph, is a fundamental challenge for graph representation learning. Yet, the dominant paradigm is ar…
Circuit-Aware SAT Solving: Guiding CDCL via Conditional Probabilities
Jiaying Zhu, Ziyang Zheng, Zhengyuan Shi +2
Circuit Satisfiability (CSAT) plays a pivotal role in Electronic Design Automation. The standard workflow for solving CSAT problems converts circuits into Conjunctive Normal Form (…
Making Slow Thinking Faster: Compressing LLM Chain-of-Thought via Step Entropy
Zeju Li, Jianyuan Zhong, Ziyang Zheng +5
Large Language Models (LLMs) using Chain-of-Thought (CoT) prompting excel at complex reasoning but generate verbose thought processes with considerable redundancy, leading to incre…
ForgeEDA: A Comprehensive Multimodal Dataset for Advancing EDA
Zhengyuan Shi, Zeju Li, Chengyu Ma +19
We introduce ForgeEDA, an open-source comprehensive circuit dataset across various categories. ForgeEDA includes diverse circuit representations such as Register Transfer Level (RT…