testbench

This paper introduces CHORUS, a post-training framework that uses staged supervised fine-tuning and reinforcement learning to create complementary expert models, which are then merged or distilled into a single 4B model that achieves 88.0% Pass@1 on the CVDP-ECov testbench stimulus generation benchmark, outperforming DeepSeek-R1.