most citedMG-Verilog: Multi-grained Dataset Towards Enhanced LLM-assisted Verilog Generation

2 citations · 4 across the 4 of their papers we have counts for

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cs.LG2025

MixGCN: Scalable GCN Training by Mixture of Parallelism and Mixture of Accelerators

Cheng Wan, Runkai Tao, Zheng Du +2

Graph convolutional networks (GCNs) have demonstrated superiority in graph-based learning tasks. However, training GCNs on full graphs is particularly challenging, due to the follo…

cs.LG2024★ 2 cited

MG-Verilog: Multi-grained Dataset Towards Enhanced LLM-assisted Verilog Generation

Yongan Zhang, Zhongzhi Yu, Yonggan Fu +2

Large Language Models (LLMs) have recently shown promise in streamlining hardware design processes by encapsulating vast amounts of domain-specific data. In addition, they allow us…