Misinformation such as fake news and rumors is a serious threat for information ecosystems
and public trust. The emergence of large language models (LLMs) has great potential to …

With the ongoing rapid adoption of Artificial Intelligence (AI)-based systems in high-stakes
domains, ensuring the trustworthiness, safety, and observability of these systems has …

The contemporary LLMs are prone to producing hallucinations, stemming mainly from the
knowledge gaps within the models. To address this critical limitation, researchers employ …

Hallucination has been widely recognized to be a significant drawback for large language
models (LLMs). There have been many works that attempt to reduce the extent of …

Large language models (LLMs) have emerged as pivotal contributors in contemporary
natural language processing and are increasingly being applied across a diverse range of …

Large language models (LMs) are prone to generate diverse factually incorrect statements,
which are widely called hallucinations. Current approaches predominantly focus on coarse …

Adapting large language models (LLMs) to new domains/tasks and enabling them to be
efficient lifelong learners is a pivotal challenge. In this paper, we propose MoRAL, ie, Mixture …

Large Language Model (LLM) based generative AI, such as ChatGPT, is considered the first
generation of Artificial General Intelligence (AGI), exhibiting zero-shot learning abilities for a …

Amidst the burgeoning information age, the rapid development of artificial intelligence-
generated content (AIGC) has brought forth challenges regarding information authenticity …

Since their inception in the 1980s, language models (LMs) have been around for more than
four decades as a means for statistically modeling the properties observed from natural …