Science

New research reveals a concerning weakness in large language models that rely on specialized ‘expert’ systems, potentially allowing attackers to bypass safety measures with surprising ease.

As digital defenses accumulate complexity and age, the cybersecurity landscape is entering a period of diminishing returns, raising critical questions about long-term resilience.

A new framework, zkFL-Health, is enabling privacy-preserving federated learning for medical AI, safeguarding sensitive data during collaborative model training.

A new framework, zkFL-Health, is leveraging cutting-edge cryptographic techniques to enable privacy-preserving federated learning for sensitive medical data.

New research reveals a surprisingly effective method for prompting large language models to generate malicious code, even those considered highly secure.

A novel mathematical approach establishes a direct link between the structure of information networks and the principles of intuitionistic logic.

Researchers have developed a novel neural speech codec that significantly reduces bandwidth requirements without sacrificing audio quality.

Researchers have developed a new framework, ESCHER, to efficiently represent and analyze evolving hypergraphs, unlocking significant speedups for key graph computations.

A new study explores whether large language models can seamlessly continue mathematical problem-solving started by another AI, revealing significant performance differences based on model architecture.

A new method breaks down the complex problem of assessing network resilience to link uncertainties into smaller, more manageable components.