Time series analysis stands as a focal point within the data mining community, serving as a
cornerstone for extracting valuable insights crucial to a myriad of real-world applications …

Large Language Models (LLMs) have seen significant use in domains such as natural
language processing and computer vision. Going beyond text, image and graphics, LLMs …

Time series analysis is essential for comprehending the complexities inherent in various real-
world systems and applications. Although large language models (LLMs) have recently …

This paper introduces a novel approach that leverages Large Language Models (LLMs) and
Generative Agents to enhance time series forecasting by reasoning across both text and …

Mobility analysis is a crucial element in the research area of transportation systems.
Forecasting traffic information offers a viable solution to address the conflict between …

Intelligent Transportation Systems (ITS) operate within a highly intricate and dynamic
environment characterized by complex spatial and temporal dynamics at various scales …

Traffic prediction constitutes a pivotal facet within the purview of Intelligent Transportation
Systems (ITS), and the attainment of highly precise predictions holds profound significance …

Transportation has greatly benefited the cities' development in the modern civilization
process. Intelligent transportation, leveraging advanced computer algorithms, could further …

Machine learning techniques are now integral to the advancement of intelligent urban
services, playing a crucial role in elevating the efficiency, sustainability, and livability of …

With the proliferation of mobile sensing techniques, huge amounts of time series data are
generated and accumulated in various domains, fueling plenty of real-world applications. In …