AI RESEARCH
Auditing Multimodal LLM Raters: Central Tendency Bias in Clinical Ordinal Scoring
arXiv CS.CV
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ArXi:2605.16386v1 Announce Type: new Multimodal large language models (LLMs) are increasingly explored as automated evaluators in clinical settings, yet their scoring behavior on ordinal clinical scales remains poorly understood. We benchmark three frontier LLM families against supervised deep learning models for scoring Clock Drawing Test (CDT) images on two public datasets using the Shulman rubric.