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CHORUS framework boosts hardware verification stimulus generation by 13.5% · arXiv

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Researchers have developed CHORUS, a novel post-training framework for generating high-coverage testbench stimuli for hardware verification. By leveraging complementary strengths from staged SFT checkpoints and dense-reward RL, CHORUS consolidates specialists into a single 4B model. This approach significantly outperforms existing methods, achieving 88.0% Pass@1 on the CVDP-ECov benchmark, a 13.5 percentage point improvement over the much larger 671B DeepSeek-R1 model. AI

RANK_REASON The cluster describes a new research paper detailing a novel framework for stimulus generation in hardware verification. [lever_c_demoted from research: ic=1 ai=1.0]

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CHORUS framework boosts hardware verification stimulus generation by 13.5% · arXiv

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The cluster describes a new research paper detailing a novel framework for stimulus generation in hardware verification. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Hejia Zhang, Sheng Lu, Zhongming Yu, Chia-Tung Ho, Brucek Khailany, Jishen Zhao ·

    CHORUS: Complementary Experts for High-Coverage Testbench Stimulus Generation

    arXiv:2608.10090v1 Announce Type: new Abstract: Large language models (LLMs) have advanced code generation, where executable feedback provides a more reliable learning signal than textual imitation alone. Hardware verification is an important application of code generation and ac…

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