Science

A new framework enables large language models to dynamically adapt to specific tasks by learning from human feedback, creating a collaborative sensemaking process.

A new framework dramatically improves data efficiency in robotic manipulation by breaking down complex tasks into reusable, independent factors.

A new benchmark, ARC-AGI-3, pushes AI systems beyond rote learning to assess their ability to efficiently acquire and generalize skills in dynamic, interactive environments.

A new framework combines the strengths of deep reinforcement learning and Bayesian inference to help robots navigate and locate objects more reliably in complex indoor spaces.

A new perspective frames artificial intelligence not as a replacement for human expertise, but as a collaborative partner enhancing shared understanding in complex care scenarios.

New research integrates thermal vision with advanced AI, enabling robots to perceive and interact with the world in a more nuanced and safe manner.

Researchers have created a challenging benchmark to test if artificial intelligence can deduce molecular structures from experimental data, mimicking the problem-solving process of a chemist.

Researchers have developed a novel framework that generates compelling human-object interaction animations without relying on traditional classifiers or complex kinematic constraints.

Researchers are developing a rigorous, category-theoretic approach to assess the structural reasoning abilities of autonomous AI systems.

Researchers have developed a novel framework for accurately perceiving and reconstructing articulated object movements from everyday videos captured by wearable cameras.