  We introduce the Curious About Uncertain Scene (CAUS) dataset, designed to
enable Large Language Models, specifically GPT-4, to emulate human cognitive
processes for resolving uncertainties. Leveraging this dataset, we investigate
the potential of LLMs to engage in questioning effectively. Our approach
involves providing scene descriptions embedded with uncertainties to stimulate
the generation of reasoning and queries. The queries are then classified
according to multi-dimensional criteria. All procedures are facilitated by a
collaborative system involving both LLMs and human researchers. Our results
demonstrate that GPT-4 can effectively generate pertinent questions and grasp
their nuances, particularly when given appropriate context and instructions.
The study suggests that incorporating human-like questioning into AI models
improves their ability to manage uncertainties, paving the way for future
advancements in Artificial Intelligence (AI).
