New research demonstrates a system where robots use both visual understanding and natural language to dynamically adjust collaborative tasks, improving reliability in human-robot interaction.
A new benchmark assesses how well artificial intelligence can independently complete full data science workflows, from initial analysis to final results.
A new framework integrates audio cues with visual and proprioceptive data, enabling more precise and robust robotic manipulation capabilities.
New research reveals how hackers are discussing and experimenting with artificial intelligence, but practical implementation remains a significant hurdle.
Researchers have developed a new framework that enables robots to generate realistic and efficient hand-object interactions by learning from sequences of fluid movements.
A new review examines how contrasting theoretical models for gamma-ray bursts and cosmic rays reveal the evolving interplay between human-led astrophysical modeling and data-driven AI approaches.
New research explores how a conversational hand-off between a social robot and a smartwatch can enhance indoor navigation and distribute cognitive effort.
New research explores how abductive reasoning can bridge the gap between artificial intelligence and human clinical expertise in identifying critical symptoms.
A new multi-agent system combines the power of large language models and systematic search to autonomously explore and validate algorithms for complex problems.
A new framework leverages the power of large language models and structured knowledge to help robots articulate their reasoning, fostering clearer communication and trust in human-robot teams.