Since the emergence of security concerns in artificial intelligence (AI), there has been
significant attention devoted to the examination of backdoor attacks. Attackers can utilize …

The advancement of large language models (LLMs) has significantly enhanced the ability to
effectively tackle various downstream NLP tasks and unify these tasks into generative …

Generative Large Language Models (LLMs) have made significant strides across various
tasks, but they remain vulnerable to backdoor attacks, where specific triggers in the prompt …

The remarkable performance of large language models (LLMs) in generation tasks has
enabled practitioners to leverage publicly available models to power custom applications …

The task of condensing large chunks of textual information into concise and structured tables
has gained attention recently due to the emergence of Large Language Models (LLMs) and …

Large Language Models (LLMs) have sparked substantial interest and debate concerning
their potential emergence of Theory of Mind (ToM) ability. Theory of mind evaluations …

Safety backdoor attacks in large language models (LLMs) enable the stealthy triggering of
unsafe behaviors while evading detection during normal interactions. The high …

The rapid advancement of large models, driven by their exceptional abilities in learning and
generalization through large-scale pre-training, has reshaped the landscape of Artificial …

Preference learning is a central component for aligning current LLMs, but this process can
be vulnerable to data poisoning attacks. To address this concern, we introduce …

The rise of large language models (LLMs) has significantly influenced the quality of
information in decision-making systems, leading to the prevalence of AI-generated content …