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

This survey addresses the crucial issue of factuality in Large Language Models (LLMs). As
LLMs find applications across diverse domains, the reliability and accuracy of their outputs …

Large language models (LLMs), exemplified by ChatGPT, have gained considerable
attention for their excellent natural language processing capabilities. Nonetheless, these …

Instruction tuning large language models (LLMs) remains a challenging task, owing to the
complexity of hyperparameter selection and the difficulty involved in evaluating the tuned …

Large language models (LLMs) have gained considerable attention for their excellent
natural language processing capabilities. Nonetheless, these LLMs present many …

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 …

Knowledge-intensive tasks (eg, open-domain question answering (QA)) require a
substantial amount of factual knowledge and often rely on external information for …

Long-context modeling capabilities of Large Language Models (LLMs) have garnered
widespread attention, leading to the emergence of LLMs with ultra-context windows …

Due to the widespread use of large language models (LLMs), we need to understand
whether they embed a specific “worldview” and what these views reflect. Recent studies …

Purpose To evaluate the capabilities and incapabilities of a GPT-4V (ision)-based chatbot in
interpreting ocular multimodal images. Methods We developed a digital ophthalmologist app …