21 citations · 22 across the 6 of their papers we have counts for
6 papers
Scaling Test-Driven Code Generation from Functions to Classes: An Empirical Study
Yunhao Liang, Ruixuan Ying, Shiwen Ni +1
Test-driven development (TDD) has been adopted to improve Large Language Model (LLM)-based code generation by using tests as executable specifications. However, existing TDD-style…
NOVA: Coordinated Test Selection and Bayes-Optimized Constrained Randomization for Accelerated Coverage Closure
Weijie Peng, Nanbing Li, Jin Luo +5
Functional verification relies on large simulation-based regressions. Traditional test selection relies on static test features and overlooks actual coverage behavior, wasting subs…
R3A: Reliable RTL Repair Framework with Multi-Agent Fault Localization and Stochastic Tree-of-Thoughts Patch Generation
Zizhang Luo, Fan Cui, Kexing Zhou +4
Repairing RTL bugs is crucial for hardware design and verification. Traditional automatic program repair (APR) methods define dedicated search spaces to locate and fix bugs with pr…
SLOTH: Lightweight Detection and Localization of On-Chip Fail-Slow Failures for DNN Accelerators
Junchi Wu, Xinfei Wan, Zhuoran Li +5
Spatial DNN accelerators are essential for high-performance inference, but their performance is undermined by widespread fail-slow failures. Detecting such failures on-chip is chal…
OriGen:Enhancing RTL Code Generation with Code-to-Code Augmentation and Self-Reflection
Fan Cui, Chenyang Yin, Kexing Zhou +9
Recent studies have demonstrated the significant potential of Large Language Models (LLMs) in generating Register Transfer Level (RTL) code, with notable advancements showcased by…
The Dawn of AI-Native EDA: Opportunities and Challenges of Large Circuit Models
Lei Chen, Yiqi Chen, Zhufei Chu +36
Within the Electronic Design Automation (EDA) domain, AI-driven solutions have emerged as formidable tools, yet they typically augment rather than redefine existing methodologies.…