A new audit reveals that leading large language models exhibit significant biases, demonstrating a limited understanding of technical indicators in the Global South and raising critical questions about equitable AI development.
New research reveals that current artificial intelligence systems struggle to accurately and urgently translate critical information during rapidly unfolding emergencies.
A new framework leverages the power of artificial intelligence to predict and prevent disruptions in critical communication infrastructure.
![An adversarial critique mechanism demonstrably enhances performance across all evaluated metrics, with observed improvements reaching statistical significance [latex] (p < 0.05) [/latex].](https://arxiv.org/html/2602.13213v1/Figuers/F8_Metric_Comparison.png)
A new approach to agentic AI leverages internal adversarial testing to dramatically improve accuracy and reliability in commercial insurance underwriting.
A new framework clarifies why 5G radio access networks might fail, enabling proactive maintenance and improved reliability.
New research reveals that advanced artificial intelligence systems demonstrate surprisingly nuanced strategic thinking when simulating high-stakes nuclear confrontations.
This review introduces a powerful framework for modeling complex financial instruments by treating them as systems for allocating stochastic cash flows.
A new analysis details the escalating risks posed by increasingly powerful artificial intelligence systems and outlines potential pathways to ensure their safe development and deployment.
As large language models infiltrate financial analysis, a critical examination of potential biases is essential for reliable results.
Current AI safety evaluations often fail to account for the unique vulnerabilities and contextual risks present in African nations, demanding a more localized approach.