Pareto-Optimal RTL Code Generation via Multi-Objective Reinforcement Learning with Large Language Models
This work is the first to propose a learning method for LLM-based circuit generation that optimizes, not the quality of a single circuit, but the quality and diversity of the entire circuit set obtained through multiple generations in the PPA objective space.
Koki Takeshita, Kenji Uebayashi, Hikaru Tomonari et al.
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