Science

A rigorous analysis of the LINE protocol reveals critical vulnerabilities, prompting the development of a fortified version with enhanced forward secrecy.

New calculations reveal insights into the structure and properties of hidden-charm pentaquarks, potentially explaining recent experimental observations and predicting new states.

A new framework for analyzing distributed systems leverages history constraints to define communication protocols and assess their computational complexity.

A new study explores how to efficiently run complex artificial intelligence models on Huawei’s Ascend NPUs by reducing the precision of their calculations.

A new perspective on distributed security argues for integrated architectures that move beyond treating core properties like privacy and accountability as separate concerns.

New research delivers a complete framework for verifying that machine learning models are truly protected against malicious data manipulation during training.

Researchers have developed an expanding fire-cylinder model to better understand the behavior of particles created in high-energy heavy-ion collisions.

New research reveals fundamental limitations in evaluating AI systems, showing that even rigorous testing can fail when subtle differences exist between training and real-world conditions.

New research reveals that the initial signs of neural network weights surprisingly endure throughout training, offering a novel pathway for model compression beyond conventional limits.

A new auditing framework reveals that even theoretically sound differential privacy implementations are vulnerable to subtle bugs that can compromise user data.