Science

A new study details the challenges of automating the entire scientific process with large language models, from initial hypothesis to published paper.

Researchers have developed a hierarchical system that breaks down complex robotic actions into understandable components, offering improved clarity and accuracy in explainable AI.

A new framework reveals how subtle changes to input prompts can dramatically alter the outputs of generative AI systems, offering crucial insights into their behavior.

Researchers are building increasingly realistic digital twins using 3D Gaussian Splatting to bridge the gap between simulation and real-world robotic manipulation.

A new review systematically maps the evolving theory behind large language models, offering a lifecycle perspective on their development and behavior.

A new framework enables robots to safely interact with objects in crowded spaces by learning how to subtly nudge and avoid collisions.

New research suggests that imbuing AI agents with the ability to dynamically manage their reasoning process – much like human cognition – is key to unlocking superior problem-solving abilities.

Researchers have developed a new framework to quantify and instill human-like qualities in artificial intelligence, moving beyond simple task completion to genuinely natural conversation.

Researchers have developed a new framework that leverages the power of artificial intelligence to translate visual and textual information into rigorously verifiable logical statements.

A new study examines the disconnect between expectations and reality in AI-driven hiring, revealing how current systems often undermine candidate agency and satisfaction.