Science

New research explores whether large language models can move beyond simple fact-checking to identify the specific evidence supporting or refuting a statement.

A new approach to text-to-image generation bypasses the need for dedicated prior networks by directly optimizing image embeddings within diffusion models.

Researchers have developed a novel method that combines expert guidance with adversarial learning to infer reward functions and optimize policies more effectively.

New research shows that language models can be trained to reliably identify concepts they’ve been taught, opening a path toward more transparent and controllable artificial intelligence.

A new technique allows aggressively compressed neural networks to regain lost performance by generating synthetic data and transferring knowledge, offering a path to efficient and privacy-preserving AI.

New research reveals that carefully selecting the most impactful data can dramatically reduce the computational cost of training machine learning models for time series analysis in telecommunications.

Researchers are leveraging the power of artificial intelligence to simplify the configuration and management of private 5G networks through natural language commands.

New research examines whether electricity suppliers manipulate bids in response to automated systems designed to prevent market abuse.

A new framework leverages stable, bidirectional graph convolutional networks and intelligent data selection to achieve high accuracy in action recognition with significantly fewer labeled examples.

Researchers have unveiled a challenging benchmark to assess how well artificial intelligence can detect increasingly sophisticated audio-video forgeries.