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aiXamine: Unified Black-Box Evaluation of Cross-Dimensional Trade-offs in LLM Safety, Security, and Privacy
arXiv cs.LG — Machine Learning
Factual evidence
What the source reports
Researchers introduced aiXamine, a black-box framework evaluating trade-offs across safety, security, and privacy in LLMs.
Open sourceOneBench interpretation
Institutional assessment
So what
Single-metric safety benchmarks mask trade-offs like high false-refusal rates and privacy leaks, exposing models to operational and compliance failures.
Do what
Ask your model risk team to review cross-dimensional failure metrics in your current evaluation harnesses for customer-facing LLMs.