Adversarial Training (AT), which adversarially perturb the input samples during training, has
been acknowledged as one of the most effective defenses against adversarial attacks, yet …

Large Language Models (LLMs) have achieved remarkable success across diverse tasks,
yet they remain vulnerable to adversarial attacks, notably the well-documented\textit …

Over the past decade, Artificial Intelligence (AI) has had great success recently and is being
used in a wide range of academic and industrial fields. More recently, Large Language …

In modern machine (ML) learning systems, Transformer-based architectures have achieved
milestone success across a broad spectrum of tasks, yet understanding their operational …

In text classifier models, the complexity of recurrent neural networks (RNNs) is very high
because of the vast state space and uncertainty of transitions, which makes the RNN …

Adversarial examples are notably characterized by their strong transferability, allowing
attackers to craft these examples on their models and subsequently deploy them against …

The resilience of leader-following structures has been a hotspot in both academic and
industrial research. Existing studies mainly focus on maintaining follower coherence, usually …

The pursuit of interpretable artificial intelligence has led to significant advancements in the
development of methods that aim to explain the decision-making processes of complex …

Artificial Intelligence (AI) has made remarkable advancements, surpassing human
capabilities in various domains. This paper delves into cutting-edge AI technologies …

Abstract Recently, the mysterious In-Context Learning (ICL) ability of Transformer
architecture, particularly in large language models, has garnered considerable research …