This research demonstrates how Large Language Models can be augmented with predictor networks to accurately estimate circuit quality without intensive computational processes.

• Combines LLMs with specialized networks to understand low-level circuit design
• Enables rapid quality estimation of logic synthesis outcomes
• Significantly reduces computational resources compared to traditional methods
• Creates new possibilities for iterative circuit design optimization

For engineering teams, this approach offers a breakthrough in chip design workflows, allowing for faster design cycles and more efficient exploration of design alternatives without the traditional computational bottlenecks.

The Graph's Apprentice: Teaching an LLM Low Level Knowledge for Circuit Quality Estimation