Science

New research demonstrates a surprisingly efficient method for reconstructing sensitive data from split neural networks, even with limited access and existing defenses.

A novel deep learning architecture combines the strengths of recurrent neural networks to achieve more accurate and nuanced sentiment classification.

New research reveals that the narrative framing of corporate earnings calls-beyond the numbers themselves-systematically influences analyst forecasts and ultimately, realized earnings.

A new deep learning approach dramatically improves our ability to identify galaxy mergers, even faint and distant ones, revealing a more complete picture of galactic evolution.

A new framework uses the power of artificial intelligence to accurately understand the reasoning behind complex transactions on decentralized finance platforms.

A new study shows that reinforcement learning agents can develop surprisingly effective trading strategies by learning directly from simulated market dynamics.

This review explores how graph neural networks are revolutionizing our ability to understand and predict traffic patterns in increasingly connected vehicular ecosystems.

Large language models are fundamentally reshaping how companies strategize, research, and adapt in a rapidly evolving market.

New research demonstrates a more effective neural network technique for generating realistic, privacy-preserving tabular datasets, addressing limitations of existing methods.

New research reveals that artificial intelligence can be used to coordinate manipulation within platforms designed to equitably divide resources, potentially undermining their intended benefits.