AI & ML · Sep 16
K-Bench hits arXiv with 125 configurations, 33 base models, 14 providers, and a frozen GPT-4o judge at 94.2% clinician agreement
A new clinician-calibrated benchmark pushes LLM safety evaluation toward multi-turn, high-risk conversations instead of prompt-card theater.
- Evaluate sensitive AI workflows with multi-turn scenarios, not single prompt demos.
- Validate LLM judges against expert consensus before trusting automated safety scores.
- Track safety-critical dimensions separately because strong overall model behavior can hide risk-specific weaknesses.