LLM-Guided Neural Architecture Search for Robust Co-Design of Physical Neural Networks
Researchers have developed a new framework called UH-NAS, which uses LLMs to guide neural architecture search for physical neural networks. This approach co-optimizes task accuracy with hardware constraints like energy consumption and physical non-idealities. UH-NAS is designed to be hardware-agnostic, allowing for fair comparisons across different computing platforms and discovering more robust architectures than traditional methods. AI