Science

Researchers have developed a new artificial intelligence system that automates the creation of complex models of biological systems, accelerating drug discovery and personalized medicine.

A new framework uses graph neural networks to assess collaborator reliability and optimize task completion in complex, multi-agent systems.

A new analysis reveals that artificial intelligence research backed by major technology companies receives disproportionately higher citation rates, but tends to operate within echo chambers and prioritize recent publications.

Researchers are developing more realistic and scalable driving simulations by focusing on how individual agents perceive and react to their surroundings.

New research shows that grounding AI coding assistants in specific project context dramatically improves their ability to help students learn and understand code.

Researchers propose a new framework for large language models that enables continuous alignment and performance enhancement without relying on ongoing human guidance.

A new framework leverages artificial intelligence to streamline the complex process of updating aging mainframe systems for the cloud era.

A new approach to managing information for generative AI systems moves beyond simple prompt engineering to offer a more robust and scalable solution.

A new framework, HiMoE-VLA, leverages a Mixture-of-Experts architecture to enable robots to better process diverse data and perform a wider range of tasks.

Researchers are exploring a new method to imbue language models with a deeper understanding of chemical reasoning by teaching them to predict reaction mechanisms.