Science

A new framework proposes ten essential criteria and a central Control-Plane to embed trust, accountability, and semantic integrity directly into the architecture of AI systems.

Researchers have developed a new framework enabling multiple AI agents to engage in realistic, spatially-aware conversations during shared viewing experiences.

A new review assesses the potential-and limitations-of using advanced artificial intelligence to gauge emotional responses from video footage of political addresses.

Researchers have developed a new framework for creating more diverse and controllable AI opponents and teammates in multi-player games, moving beyond rigid, pre-programmed behaviors.

Researchers introduce a new benchmark, WorldLens, designed to comprehensively evaluate how well generative models can create realistic and predictable virtual environments for autonomous driving.

Researchers have developed a framework capable of generating realistic and diverse animal movements directly from text descriptions, regardless of skeletal structure.

A new autonomous agent, DynaMate, is streamlining biomolecular simulations by intelligently designing and executing complete workflows.

A new approach uses the power of large language models to understand and recommend items with limited user interaction data, addressing a critical challenge in modern recommendation systems.

New research offers a pathway to understanding and controlling the latent concepts that drive generative models, moving beyond the ‘black box’ problem in artificial intelligence.

New research reveals the challenges of deploying machine learning models for human activity recognition when training data doesn’t reflect the behavioral patterns of older adults.