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cs.LG2025
VeriDispatcher: Multi-Model Dispatching through Pre-Inference Difficulty Prediction for RTL Generation Optimization
Zeng Wang, Weihua Xiao, Minghao Shao +4
Large Language Models (LLMs) show strong performance in RTL generation, but different models excel on different tasks because of architecture and training differences. Prior work m…
cs.LG2025★ 1 cited
SALAD: Systematic Assessment of Machine Unlearning on LLM-Aided Hardware Design
Zeng Wang, Minghao Shao, Rupesh Karn +6
Large Language Models (LLMs) offer transformative capabilities for hardware design automation, particularly in Verilog code generation. However, they also pose significant data sec…
cs.LG2024
LLMs and the Future of Chip Design: Unveiling Security Risks and Building Trust
Zeng Wang, Lilas Alrahis, Likhitha Mankali +2
Chip design is about to be revolutionized by the integration of large language, multimodal, and circuit models (collectively LxMs). While exploring this exciting frontier with trem…