Science

A new approach using contrastive learning significantly improves the detection of AI-generated images and identifies their origins, even with limited examples.

A new approach uses graph neural networks to automatically balance and optimize the complex patterns needed for modern microchip design.

New research demonstrates that advanced artificial intelligence techniques can significantly improve the clarity of weak gravitational lensing maps, paving the way for more precise cosmological measurements.

New research details a robust framework for protecting AI agents from increasingly sophisticated prompt injection attacks, ensuring reliable and secure operation.

A new approach leverages generative AI to automatically create training data for accurately segmenting and understanding centuries-old maps.

A new framework leverages the power of sequential data modeling to deliver more relevant advertising and services in the financial sector.

A new framework efficiently compresses large vision-language-action datasets into smaller, more manageable sets for training robot learning models.

Researchers have developed an end-to-end artificial intelligence pipeline leveraging spiking neural networks to effectively filter out unwanted radio interference and enhance the clarity of astronomical data.

Researchers have developed a novel deep learning model capable of both detecting and recovering concealed information embedded within images using the APVD steganographic technique.

A new framework leverages the power of graph diffusion models to generate realistic and actionable counterfactual explanations for graph-structured data.