3 papers
cs.DC2026
Towards Training Private LLMs: Exploring Fine-Tuning Language Models on Apple Silicon with RDMA over Thunderbolt
En-Ming Huang, Yao-Ting Hsieh, Hsiang-Yu Tsou +3
Private large language model (LLM) fine-tuning is increasingly important for organizations that need to adapt models using sensitive data, but it often exceeds the memory capacity…
cs.AI2026
Structured Testbench Generation for LLM-Driven HDL Design and Verification-Oriented Data Curation
En-Ming Huang, Yu-Hung Kao, Ren-Hao Deng +10
Automated testbench generation has become a critical bottleneck in large language model (LLM)-driven Register Transfer Level (RTL) workflows, where large numbers of candidate desig…
cs.AI2026
EvolVE: Evolutionary Search for LLM-based Verilog Generation and Optimization
Wei-Po Hsin, Ren-Hao Deng, Yao-Ting Hsieh +2
Verilog's design cycle is inherently labor-intensive and necessitates extensive domain expertise. Although Large Language Models (LLMs) offer a promising pathway toward automation,…