Communications of the ACM

The End of ‘Frozen’ LLMs?

Today’s standard operating procedure for LLMs involves offline training, rigorous alignment testing, and deployment with frozen weights to ensure stability. Nick Bostrom, a leading AI philosopher and ...
IEEE

Contrastive and Dual Adversarial Representation Learning for Multi-View Clustering

Abstract: Multi-View Clustering (MVC) has gained increasing attention due to its ability to effectively leverage the complementary information of multi-view data. Despite the success of existing MVC ...
IEEE

Resilient Federated Adversarial Learning With Auxiliary-Classifier GANs and Probabilistic Synthesis for Heterogeneous Environments

Abstract: Recently, collaborative learning paradigms like Federated Learning (FL) are gaining significant attention as a means of deploying artificial intelligence (AI)-based Internet of Things (IoT) ...
unite

What Is Adversarial Poetry? A New AI Jailbreak Method

Artificial intelligence (AI) safety has turned into a constant cat-and-mouse game. As developers add guardrails to block harmful requests, attackers continue to try new ways to circumvent them. One of ...
EurekAlert!

Rice algorithms take on quantum adversary

HOUSTON – (Sept. 3, 2025) – Quantum computers promise enormous computational power, but the nature of quantum states makes computation and data inherently “noisy.” Rice University computer scientists ...
Frontiers

MeetSafe: enhancing robustness against white-box adversarial examples

Convolutional neural networks (CNNs) are vulnerable to adversarial attacks in computer vision tasks. Current adversarial detections are ineffective against white-box attacks and inefficient when deep ...
The New York Times

Justice Dept. Abruptly Escalates Pressure Campaign on a Trump Adversary

Letitia James, New York’s attorney general and a longtime nemesis of the president, is being investigated in two separate inquiries, in a remarkable use of executive power to pursue a foe. By Jonah E.
Scientific Research Publishing

Standen, M., Kim, J. and Szabo, C. (2025) Adversarial Machine Learning Attacks and Defences in Multi-Agent Reinforcement Learning. ACM Computing Surveys, 57, 1-35.

ABSTRACT: To provide quantitative analysis of strategic confrontation game such as cross-border trades like tariff disputes and competitive scenarios like auction bidding, we propose an alternating ...
unite

Paul Reid, VP of Adversary Research at AttackIQ – Interview Series

Paul Reid, VP of Adversary Research at AttackIQ, is a seasoned veteran of the fast-paced world of cybersecurity. With more than two decades of experience as a technology strategist for leading tech ...