Science

New research identifies how to enhance the resilience of graph-based AI systems by strategically balancing network structure and node characteristics.

Researchers have developed a novel graph neural network solver that seamlessly integrates the strengths of traditional numerical methods with the power of modern machine learning to tackle challenging hyperbolic conservation laws.

New research introduces a framework to significantly enhance the reliability of sentiment predictions derived from large language models by focusing on syntactic and semantic consistency.

New research reveals that the way large language models reason fundamentally alters their internal dynamics, creating predictable patterns in their hidden states.

A new study explores whether large language models can accurately adjudicate disagreements arising in decentralized prediction markets like Polymarket.

New research demonstrates how neural networks can more accurately assess the worth of individual pieces on the chessboard, paving the way for stronger chess engines.

Researchers are leveraging artificial intelligence to create detailed maps of carbon monoxide emissions, revealing the structure of molecular clouds within our galaxy.

A new workflow leverages the power of artificial intelligence to automatically identify and protect sensitive information within detailed accident reports.

A new study demonstrates how artificial intelligence can translate free-text accident descriptions into visual crash diagrams, streamlining traffic safety analysis.

New research explores how to accurately predict vulnerability sightings even with limited data, a crucial task for proactive cybersecurity.