T2D-Bench: Evidence-Gated Evaluation of LLM Outputs for Type 2 Diabetes Using a Multi-Layer Clinical-Lifestyle Knowledge Graph

T2D-Bench is a new benchmark and evaluation framework designed to assess the compliance of large language model (LLM) outputs with explicit clinical guidelines for type 2 diabetes, utilizing a multi-layer clinical-lifestyle knowledge graph. It integrates biomedical data sources and ADA Standards of Care rules to evaluate LLM performance against 100 structured vignettes, revealing that baseline outputs from models like GPT-4o-mini and GPT-4 failed evidence-path checks in 35% and 33% of cases, respectively. This framework enables practitioners to identify and rectify unsupported clinical omissions in LLM-generated recommendations, enhancing their reliability in medical contexts.