MedLayBench-V: A Large-Scale Benchmark for Expert-Lay Semantic Alignment in Medical Vision Language Models (2026.findings-acl)
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| Challenge: | Medical Vision-Language Models are predominantly trained on professional literature, limiting their ability to communicate findings in the lay register required for patient-centered care. |
| Approach: | They propose a multimodal benchmark dedicated to expert-lay semantic alignment that enforces strict semantic equivalence by integrating unified medical language system (UMS) Concept Unique Identifiers (CUIs) with micro-level entity constraints. |
| Outcome: | The proposed benchmark enforces strict semantic equivalence by integrating unified medical language system (UMLS) Concept Unique Identifiers (CUIs) with micro-level entity constraints. |
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