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Abrar Alotaibi

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#artificial intelligence Preprint Aug 2026

Layered LLM Defenses as an Ensemble: Access Tiers, Inference Cost, and the Measured Failure Correlation Between Defense Layers

How a stack behaves, and the quantities a defender cares about diverge: coverage saturates within a tier, cost rises by class, false refusals accumulate as a union, and residual attack success falls multiplicatively only under independence.

Abrar Alotaibi, M. S. Jabbar, Sadam Al-Azani et al. · 0 citations
Open access Jun 2026

A red teaming framework for large language models: a case study on faithfulness evaluation

A red teaming framework that systematically uncovers vulnerabilities in LLM outputs and provides both actionable insights into current LLM vulnerabilities and a scalable methodology for ongoing safety evaluation as models continue to evolve is presented.

Abrar Alotaibi, Raed Mughus, Moataz Ahmed · 1 citation

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