# Pareto-Optimal RTL Code Generation via Multi-Objective Reinforcement Learning with Large Language Models

**Published:** October 21, 2026
**Author:** Koki Takeshita, Kenji Uebayashi, Hikaru Tomonari, Masaya Tsunokake, Koichiro Yawata, Tatsuya Sasaki, Yusuke Ohtsubo, Kota Dohi, Yasuhiro Sogawa
**Source:** arXiv — cs.AI
**Language:** en-US
**HTML:** https://aiqazaqstan.com/en/articles/pareto-optimal-rtl-code-generation-via-multi-objective-reinforcement-lea

arXiv:2610.26904v1 Announce Type: new Abstract: Recent studies have proposed reinforcement learning with verifiable rewards (RLVR) methods that enable LLMs to generate high-quality RTL circuits from natural-language specifications. Existing approaches optimize circuit PPA…

> From the original source: **arXiv — cs.AI**
> [Read full article at arXiv — cs.AI](https://arxiv.org/abs/2610.26904)

**Tags:** #arXiv

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