Science

A new analysis frames the strengths and weaknesses of transformer models through the principles of graph neural networks, shedding light on their internal workings.

Researchers are building artificial intelligence agents powered by large language models and external knowledge to deliver more accurate, consistent, and transparent financial decisions.

Understanding how attackers react to ambiguous information can significantly improve cybersecurity strategies beyond traditional loss aversion models.

New research leverages a fundamental probability theorem to provide an early warning system for changes in financial market behavior.

Researchers are leveraging the power of deep learning to identify and block command-and-control traffic from malware using algorithmically generated domain names.

Researchers have developed a novel counterfactual analysis method for spectrum auctions that proves incorporating deployment obligations can expand broadband access without sacrificing revenue.

Researchers are using explainable AI to pinpoint and correct imperfections in images created by diffusion models, leading to more realistic and refined results.

Researchers are boosting the resilience of deepfake detectors with a novel training technique that improves performance and efficiency across a wide range of generated content.

A new technique boosts the accuracy of information retrieval from complex financial filings by leveraging large language models to improve semantic search.

A new framework leverages specialized learning and structural analysis to provide more human-centric explanations for how graph neural networks arrive at their decisions.