Science

Attackers are increasingly leveraging the hype around generative AI to disguise harmful browser extensions as legitimate tools.

A new analysis argues that large language models don’t reason so much as statistically predict the most plausible continuation of a given prompt.

A new study systematically investigates the potential of reinforcement learning to overcome key challenges in generating high-quality 3D models from text prompts.

New research demonstrates how sparse autoencoders can create easily understood representations of text, offering powerful tools for data analysis.

A new method, DCFO, clarifies why data points are flagged as outliers by the Local Outlier Factor algorithm, addressing key limitations in existing explanation techniques.

Researchers have developed a method that prompts large language models to reason backwards from potential answers, revealing gaps in incomplete questions and improving problem-solving abilities.

A new framework combines dynamic neural networks and adversarial learning to dramatically improve intrusion detection in next-generation wireless systems.

Researchers have created a rigorous benchmark to evaluate how well AI can identify deepfakes and, crucially, explain why it made that determination.

Researchers are pioneering a system that seamlessly blends advertising into AI-generated text, moving beyond traditional ad placement.

A novel machine learning framework leverages the power of galaxy data to unlock accurate cosmological insights, even across different simulation types.