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Mobility Foundation Models (MFMs) have advanced the modeling of human movement patterns, yet they face a ceiling due to limitations in data scale and semantic understanding. While Large Language Models (LLMs) offer powerful semantic…

Machine Learning · Computer Science 2026-04-14 Fanjin Meng , Yuan Yuan , Jingtao Ding , Jie Feng , Chonghua Han , Yong Li

With the advancement of large language models, language-based forecasting has recently emerged as an innovative approach for predicting human mobility patterns. The core idea is to use prompts to transform the raw mobility data given as…

Artificial Intelligence · Computer Science 2024-03-07 Hao Xue , Tianye Tang , Ali Payani , Flora D. Salim

This paper explores the potential of large language models (LLMs) as reliable analytical tools in linguistic research, focusing on the emergence of affective meanings in temporal expressions involving manner-of-motion verbs. While LLMs like…

Computation and Language · Computer Science 2025-07-15 Rosa Illan Castillo , Javier Valenzuela

The advent of large language models (LLMs) presents new opportunities for travel demand modeling. However, behavioral misalignment between LLMs and humans presents obstacles for the usage of LLMs, and existing alignment methods are…

Artificial Intelligence · Computer Science 2025-05-27 Tianming Liu , Manzi Li , Yafeng Yin

Full integration of robots into real-life applications necessitates their ability to interpret and execute natural language directives from untrained users. Given the inherent variability in human language, equivalent directives may be…

Robotics · Computer Science 2025-04-08 Eran Beeri Bamani , Eden Nissinman , Rotem Atari , Nevo Heimann Saadon , Avishai Sintov

Train delays can propagate rapidly throughout the Urban Rail Transit (URT) network under networked operation conditions, posing significant challenges to operational departments. Accurately predicting passenger travel choices under train…

Machine Learning · Computer Science 2024-10-02 Chen Chen , Yuxin He , Hao Wang , Jingjing Chen , Qin Luo

A key challenge in transportation planning is that the collective preferences of heterogeneous travelers often diverge from the policies produced by model-driven decision tools. This misalignment frequently results in implementation delays…

Computers and Society · Computer Science 2025-10-29 Xiaoyu Yan , Tianxing Dai , Yu Marco Nie

Large Language Models (LLMs) are important tools for reasoning and problem-solving, while they often operate passively, answering questions without actively discovering new ones. This limitation reduces their ability to simulate human-like…

Computational Engineering, Finance, and Science · Computer Science 2025-09-26 Hong Su

Nowadays mobile communication is growing fast in the 5G communication industry. With the increasing capacity requirements and requirements for quality of experience, mobility prediction has been widely applied to mobile communication and…

Machine Learning · Computer Science 2021-11-15 Donglin Wang , Qiuheng Zhou , Sanket Partani , Anjie Qiu , Hans D. Schotten

Predicting group behavior, how individuals coordinate, communicate, and interact during collaborative tasks, is essential for designing systems that can support team performance through real-time prediction and realistic simulation of…

Human-Computer Interaction · Computer Science 2026-04-13 Diana Romero , Xin Gao , Daniel Khalkhali , Salma Elmalaki

Various methods have been proposed for utilizing Large Language Models (LLMs) in autonomous driving. One strategy of using LLMs for autonomous driving involves inputting surrounding objects as text prompts to the LLMs, along with their…

This systematic literature review comprehensively examines the application of Large Language Models (LLMs) in forecasting and anomaly detection, highlighting the current state of research, inherent challenges, and prospective future…

Machine Learning · Computer Science 2024-02-19 Jing Su , Chufeng Jiang , Xin Jin , Yuxin Qiao , Tingsong Xiao , Hongda Ma , Rong Wei , Zhi Jing , Jiajun Xu , Junhong Lin

The rapid advancement of Large Language Models (LLMs) has opened new possibilities in Multi-Robot Systems (MRS), enabling enhanced communication, task allocation and planning, and human-robot interaction. Unlike traditional single-robot and…

Robotics · Computer Science 2026-05-05 Peihan Li , Zijian An , Shams Abrar , Lifeng Zhou

With the rapid development of artificial intelligence, large language models (LLMs) have shown promising capabilities in mimicking human-level language comprehension and reasoning. This has sparked significant interest in applying LLMs to…

Computation and Language · Computer Science 2023-11-06 Mingze Yuan , Peng Bao , Jiajia Yuan , Yunhao Shen , Zifan Chen , Yi Xie , Jie Zhao , Yang Chen , Li Zhang , Lin Shen , Bin Dong

Predicting future events is an important activity with applications across multiple fields and domains. For example, the capacity to foresee stock market trends, natural disasters, business developments, or political events can facilitate…

Computation and Language · Computer Science 2025-01-13 Petraq Nako , Adam Jatowt

Large-scale human mobility simulation is critical for applications such as urban planning, epidemiology, and transportation analysis. Recent works treat large language models (LLMs) as human agents to simulate realistic mobility behaviors…

Artificial Intelligence · Computer Science 2026-02-20 Hua Yan , Heng Tan , Yingxue Zhang , Yu Yang

Large language models (LLMs) are a class of language models that have demonstrated outstanding performance across a range of natural language processing (NLP) tasks and have become a highly sought-after research area, because of their…

Digital Libraries · Computer Science 2023-04-06 Lizhou Fan , Lingyao Li , Zihui Ma , Sanggyu Lee , Huizi Yu , Libby Hemphill

Large Language Models (LLMs) are poised to play an increasingly important role in our lives, providing assistance across a wide array of tasks. In the geospatial domain, LLMs have demonstrated the ability to answer generic questions, such…

Computation and Language · Computer Science 2024-11-13 Pasquale Balsebre , Weiming Huang , Gao Cong

Traffic flow forecasting aims to predict future traffic flows based on the historical traffic conditions and the road network. It is an important problem in intelligent transportation systems, with a plethora of methods been proposed.…

Machine Learning · Computer Science 2025-08-04 Yusheng Zhao , Xiao Luo , Haomin Wen , Zhiping Xiao , Wei Ju , Ming Zhang

The rapid evolution of large language models (LLMs) and their capacity to simulate human cognition and behavior has given rise to LLM-based frameworks and tools that are evaluated and applied based on their ability to perform tasks…

Computation and Language · Computer Science 2024-12-03 Jing Yi Wang , Nicholas Sukiennik , Tong Li , Weikang Su , Qianyue Hao , Jingbo Xu , Zihan Huang , Fengli Xu , Yong Li