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Scalable Stewardship of an LLM-Assisted Clinical Benchmark with Physician Oversight

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学术前沿 5.0 分 — 中等质量:常规学术论文,有适度参考价值
原文: cs.AI updates on arXiv.org

评分 5.0 · 来源:cs.AI updates on arXiv.org · 发布于 2026-04-14

评分依据:中等质量:常规学术论文,有适度参考价值

Scalable Stewardship of an LLM-Assisted Clinical Benchmark with Physician Oversight

arXiv:2512.19691v3 Announce Type: replace Abstract: Reference labels for machine-learning benchmarks are increasingly synthesized with LLM assistance, but their reliability remains underexamined. We audit MedCalc-Bench, a clinical benchmark for medical score computation whose labels were partly derived with LLM assistance, and develop a scalable physician-in-the-loop stewardship pipeline to reassess them. At least 27% of test labels are likely erroneous or incomputable. On a 50-instance subset…