Science

New research reveals that successful integration of generative AI in higher education relies on significant, often unseen, effort from users adapting the technology to complex organizational realities.

A new approach leverages the power of large language models to dramatically improve the precision of composed image retrieval, moving beyond simple keyword matching.

Researchers have developed a novel AI framework that leverages chemical building blocks and reinforcement learning to generate promising new drug candidates.

Researchers have developed a system that proactively safeguards embodied AI agents by combining reasoning and executable safety protocols to prevent accidents and ensure reliable operation.

This research details the development of a robust relative localization system enabling accurate positioning for modular, self-reconfigurable robots.

A new framework leverages incentive compatibility and differentiable pricing to achieve guaranteed coordination in multi-agent systems, overcoming limitations of traditional AI.

Researchers are demonstrating how large language models can translate everyday commands into complex movement plans for quadruped robots, opening the door to more intuitive robot control.

New research reveals that large language models can be easily misled by semantic interference, exposing fundamental limitations in their ability to truly reason and perform even simple calculations.

Integrating a robot’s sense of its own movement improves the accuracy of AI models that describe its actions in language.

A new system leverages artificial intelligence and multimodal data analysis to accelerate and improve initial candidate screening.