ReproBridge lifts ML reproduction to 92.6%

ReproBridge makes a strong case that agent reliability depends as much on artifact quality and handoffs as on model capability. The results are promising, though the benchmark bundles artifact construction with the resulting workflow.

• –ReproBridge-Bench covers 387 experiments across 36 papers with independently checked execution evidence
• –All four evaluated models exceeded 90% mean success with refined artifacts
• –Environment setup and cleaned-up code produced the largest gains in ablation tests
• –Lower API spending suggests reproducibility improvements can also reduce research automation costs
• –Teams should validate the workflow on their own repositories before treating 92.6% as a general guarantee