Bridging the Knowledge Gap: How Humans and AI Can Seek Information Together
A new framework proposes modeling the capabilities of diverse knowledge sources to improve collaborative information seeking between people and artificial intelligence.
A new framework proposes modeling the capabilities of diverse knowledge sources to improve collaborative information seeking between people and artificial intelligence.

A new interactive system empowers economists to rapidly translate intuitive ideas into executable agent-based models, accelerating the pace of research and enhancing rigor.

A new approach analyzes the building blocks of human movements to predict actions earlier and more reliably, paving the way for safer and more intuitive robot collaboration.
A new framework treats artificial agents as models of human cognition, allowing researchers to statistically evaluate how underlying cognitive processes drive behavior.
Researchers have demonstrated an artificial intelligence agent capable of independently designing and executing experiments on a physical optical system, leading to the discovery of a previously unknown interaction.

Researchers have unveiled OmniRobotHome, a multi-camera system designed to facilitate natural, real-time interaction between people and robots in everyday home environments.
This review explores how robots can acquire complex manipulation skills by observing and interpreting human demonstrations in video.
![The method defines collective knowledge as a tuple encompassing the best estimate [latex]b[/latex], evidence [latex]e[/latex], best theory [latex]t\_{best}[/latex], and its corresponding natural language analysis result [latex]\mathcal{R}[/latex], enabling the discovery of governing equations for previously unknown scientific systems through symbolic reasoning.](https://arxiv.org/html/2604.27297v1/x2.png)
A new approach combines the power of artificial intelligence with symbolic reasoning to automatically discover the underlying laws governing complex systems.

A new wave of mathematically rigorous AI tools is poised to transform wireless communication, moving beyond empirical performance to provable guarantees and novel theoretical discoveries.

New research shows that simplified sensor data can be just as effective – and more efficient – for preventing collisions in complex humanoid robots.