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 …

This paper explores the evolution of geoscientific inquiry, tracing the progression from
traditional physics-based models to modern data-driven approaches facilitated by significant …

The application of machine learning (ML) in a range of geospatial tasks is increasingly
common but often relies on globally available covariates such as satellite imagery that can …

Large language models (LLMs) exhibit impressive capabilities across diverse tasks in
natural language processing. Nevertheless, challenges arise such as large model …

Large Language Models (LLMs) inherently carry the biases contained in their training
corpora, which can lead to the perpetuation of societal harm. As the impact of these …

Understanding knowledge mechanisms in Large Language Models (LLMs) is crucial for
advancing towards trustworthy AGI. This paper reviews knowledge mechanism analysis …

Urban environments, characterized by their complex, multi-layered networks encompassing
physical, social, economic, and environmental dimensions, face significant challenges in the …

Large language models (LLMs) have achieved huge success for their general knowledge
and ability to solve a wide spectrum of tasks in natural language processing (NLP). Due to …

This paper embarks on an exploration into the Large Language Model (LLM) datasets,
which play a crucial role in the remarkable advancements of LLMs. The datasets serve as …

\label {sec: abstract} Large Language Models (LLMs) have shown promise in assisting
scientific discovery. However, such applications are currently limited by LLMs' deficiencies in …