Science

New research reveals that the performance gains from prompting large language models to ‘think step-by-step’ aren’t always reliable, and understanding why is key to building more robust AI coding tools.

A new approach utilizes nested lattice codes built on multiquadratic fields to enhance the reliability and secrecy of communications in challenging wireless environments.

A new evaluation of the Crypto-Agility Maturity Model reveals both its potential and the challenges of preparing IT systems for future cryptographic threats.

A new framework tackles the challenge of deploying large language models on resource-constrained hardware through intelligent quantization techniques.

A new analysis reveals that strategically altering code during runtime can create a moving target, dramatically increasing the difficulty of successful software tampering.

Researchers demonstrate a functional system for performing privacy-preserving inference with large language models using advanced encryption techniques.

New research clarifies the trade-offs between combining multiple statistical problems and maintaining reliable, replicable results.

Researchers have developed a novel technique that streamlines the process of deploying large language models with Mixture-of-Experts architectures in low-precision formats.

Researchers have developed a method to prevent large language models from getting stuck in repetitive loops, improving the quality and diversity of extended outputs.

Researchers have successfully demonstrated a quantum protocol inspired by traversable wormholes, bringing us closer to experimentally verifying theories linking quantum entanglement and spacetime geometry.