Large language models (LLMs) are gaining increasing popularity in both academia and
industry, owing to their unprecedented performance in various applications. As LLMs …

We envision" AI scientists" as systems capable of skeptical learning and reasoning that
empower biomedical research through collaborative agents that integrate AI models and …

Empowering large language models to accurately express confidence in their answers is
essential for trustworthy decision-making. Previous confidence elicitation methods, which …

Do large language models (LLMs) know the law? LLMs are increasingly being used to
augment legal practice, education, and research, yet their revolutionary potential is …

Widely deployed large language models (LLMs) can produce convincing yet incorrect
outputs, potentially misleading users who may rely on them as if they were correct. To …

Large Vision-Language Models (LVLMs) have recently achieved remarkable success.
However, LVLMs are still plagued by the hallucination problem, which limits the practicality …

When large language models are aligned via supervised fine-tuning, they may encounter
new factual information that was not acquired through pre-training. It is often conjectured that …

Despite efforts to expand the knowledge of large language models (LLMs), knowledge gaps-
-missing or outdated information in LLMs--might always persist given the evolving nature of …

Recent research has made significant strides in applying alignment techniques to enhance
the helpfulness and harmlessness of large language models (LLMs) in accordance with …

In recent years, there have been remarkable advancements in node classification achieved
by Graph Neural Networks (GNNs). However, they necessitate abundant high-quality labels …