LATIDIA · Investigación

MedBenchAgent: Hacia la automatización sistemática de la construcción de puntos de referencia de VLM médicos

arXiv: 2610.11312v1Tipo de anuncio: nuevo Resumen: La construcción a gran escala de puntos de referencia del modelo médico de visión y lenguaje (VLM) es cada vez más factible con conjuntos de datos de imágenes ricamente anotados y modelos de lenguaje grandes (LLM),

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arXiv:2610.11312v1 Announce Type: new Abstract: Large-scale construction of medical vision-language model (VLM) benchmarks is increasingly feasible with richly annotated imaging datasets and large language models (LLMs), yet existing automation largely focuses on generating evaluation items within predefined benchmark specifications. We study the broader problem of automatically deriving the specification itself: what to evaluate, which annotations support each task, and how to translate this evidence into reliable evaluation items. We formulate benchmark construction as constrained compilation, in which the benchmark specification is progressively derived from evaluation requirements, heterogeneous annotations, and medical knowledge. Based on this formulation, we introduce MedBenchAgent, a multi-agent framework with a Benchmark Intermediate Representation (BIR) that encodes task