LLM Robustness Failures Under Adversarial and Out-of-Distribution Inputs

Executive Summary

Large language models degrade in quality and reliability when exposed to unexpected, adversarial, or out-of-distribution inputs, revealing critical gaps in operational resilience. Without structured robustness evaluation, boards cannot assure that deployed models will perform safely under real-world conditions.