Science

A novel framework, Polynomiogram, bridges the gap between complex mathematical analysis and striking visual aesthetics.

A new model extends the Segment Anything capabilities by directly interpreting natural language instructions, bridging the gap between vision and language for precise image segmentation.

Researchers have developed a powerful artificial intelligence model capable of both understanding and generating molecular structures, accelerating possibilities in chemical informatics and drug discovery.

A new study demonstrates that combining the strengths of multiple artificial intelligence models can significantly enhance the accuracy and reliability of medication recommendations derived from patient clinical notes.

New research demonstrates a method for automatically converting abstract AI governance policies into concrete, verifiable rules for implementation.

As AI-synthesized videos become increasingly realistic, accurately assessing the naturalness of human movement within them remains a significant challenge.

A new framework, POLARIS, explores how multi-agent AI can move beyond reactive self-adaptation to systems that proactively reason about and optimize their responses to changing conditions.

New research reveals a trade-off in AI-powered question answering systems, where tailoring responses to individual users boosts reasoning ability but often reduces their overall semantic similarity to standard answers.

A new reinforcement learning approach focuses on identifying and refining the most impactful actions in multi-step problem-solving agents, leading to significant gains in efficiency and success.

Researchers have developed a new approach enabling robots to seamlessly combine locomotion and manipulation tasks, paving the way for more versatile and adaptable robotic systems.