RTL-BenchMT: Dynamic Maintenance of RTL Generation Benchmark Through Agent-Assisted Analysis and Revision
The paper introduces RTL-BenchMT, an automated framework for maintaining RTL generation benchmarks. It addresses challenges such as flawed benchmark cases and overfitting, which are difficult to resolve manually. The framework aims to reduce human maintenance costs and will provide an open-sourced refined benchmark suite for the community.
- ▪RTL-BenchMT is designed to automatically identify and revise flawed benchmark cases.
- ▪The framework also detects and updates overfitting cases in RTL benchmarks.
- ▪The refined benchmark suite produced by RTL-BenchMT will be open-sourced to the community.
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Computer Science > Artificial Intelligence arXiv:2605.15537 (cs) [Submitted on 15 May 2026] Title:RTL-BenchMT: Dynamic Maintenance of RTL Generation Benchmark Through Agent-Assisted Analysis and Revision Authors:Jing Wang, Shang Liu, Hangan Zhou, Zhiyao Xie View a PDF of the paper titled RTL-BenchMT: Dynamic Maintenance of RTL Generation Benchmark Through Agent-Assisted Analysis and Revision, by Jing Wang and 3 other authors View PDF HTML (experimental) Abstract:This paper introduces RTL-BenchMT, an agentic framework for dynamically maintaining RTL generation benchmarks. Large Language Models (LLMs) assisted automated RTL generation is one of the most important directions in EDA research.
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