arXiv AI By Yulin Fu (Beijing University of Posts and Telecommunications), Junren Wang (West China Hospital, Sichuan Provincial Engineering Research Center of Intelligent Diagnosis and Treatment of Breast Diseases), Guangjing Yang (Beijing University of Posts and Telecommunications), Zhangyuan Yu (Beijing University of Posts and Telecommunications), Wanran Sun (Beijing University of Posts and Telecommunications), Jiabao Zhou (Beijing University of Posts and Telecommunications), Jin Yin (West China Hospital, Sichuan Provincial Engineering Research Center of Intelligent Diagnosis and Treatment of Breast Diseases), Qicheng Lao (Beijing University of Posts and Telecommunications)

MedBenchAgent: Towards Systematic Automation of Medical VLM Benchmark Construction

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MedBenchAgent is a multi‑agent framework that automates the entire process of constructing medical vision‑language model benchmarks, from deriving the benchmark specification to generating and auditing evaluation items. It uses a Benchmark Intermediate Representation (BIR) to encode task definitions, evidence mappings, evaluation protocols, and item specifications, separating planning from instantiation. The system achieves a Task‑Space F1 of 90.9% and demonstrates high audit pass rates, outperforming existing task induction methods and showing portability across specialized medical domains.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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