Researchers have developed a novel framework, BugSweeper, that leverages graph neural networks to pinpoint vulnerabilities within smart contract code with greater precision.
Researchers are harnessing the power of machine learning to isolate the faint signals from the universe’s first stars and galaxies.
Researchers have demonstrated a novel method for deceiving AI-powered image detectors, highlighting critical vulnerabilities in current authentication systems.
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.