Science

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.

A new hierarchical modeling approach dramatically improves the speed and memory efficiency of processing lengthy text sequences.