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Related papers: Harnessing LLMs for Cross-City OD Flow Prediction

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Out-of-Distribution (OOD) detection is a critical task that has garnered significant attention. The emergence of CLIP has spurred extensive research into zero-shot OOD detection, often employing a training-free approach. Current methods…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Haoran Xu , Yanlin Liu , Zizhao Tong , Jiaze Li , Kexue Fu , Yuyang Zhang , Longxiang Gao , Shuaiguang Li , Xingyu Li , Yanran Xu , Changwei Wang

Semantic communication is a promising technology for next-generation wireless networks. However, the out-of-distribution (OOD) problem, where a pre-trained machine learning (ML) model is applied to unseen tasks that are outside the…

Signal Processing · Electrical Eng. & Systems 2024-07-23 Feifan Zhang , Yuyang Du , Kexin Chen , Yulin Shao , Soung Chang Liew

Predicting the future trajectories of dynamic traffic actors is a cornerstone task in autonomous driving. Though existing notable efforts have resulted in impressive performance improvements, a gap persists in scene cognitive and…

Computer Vision and Pattern Recognition · Computer Science 2024-05-09 Zhengxing Lan , Hongbo Li , Lingshan Liu , Bo Fan , Yisheng Lv , Yilong Ren , Zhiyong Cui

The estimation of origin-destination (OD) matrices is a crucial aspect of Intelligent Transport Systems (ITS). It involves adjusting an initial OD matrix by regressing the current observations like traffic counts of road sections (e.g.,…

Artificial Intelligence · Computer Science 2023-10-10 Zheli Xiong , Defu Lian , Enhong Chen , Gang Chen , Xiaomin Cheng

Service-level mobile traffic prediction for individual users is essential for network efficiency and quality of service enhancement. However, current prediction methods are limited in their adaptability across different urban environments…

Machine Learning · Computer Science 2025-07-25 Shiyuan Zhang , Tong Li , Zhu Xiao , Hongyang Du , Kaibin Huang

This study seeks to utilize large language models (LLMs) to forecast the moving ports of fluid antenna (FA). By repositioning the antenna to the locations identified by our proposed model, we intend to address the mobility challenges faced…

Signal Processing · Electrical Eng. & Systems 2025-09-03 Yali Zhang , Haifan Yin , Weidong Li , Emil Bjornson , Merouane Debbah

Traffic prediction plays a central role in intelligent transportation systems (ITS) by supporting real-time decision-making, congestion management, and long-term planning. However, many existing approaches face practical limitations. Most…

Machine Learning · Computer Science 2026-04-21 Seerat Kaur , Sukhjit Singh Sehra , Dariush Ebrahimi

Language models (LMs) are machine learning models designed to predict linguistic patterns by estimating the probability of word sequences based on large-scale datasets, such as text. LMs have a wide range of applications in natural language…

Out-of-distribution (OOD) detection plays a vital role in enhancing the reliability of machine learning (ML) models. The emergence of large language models (LLMs) has catalyzed a paradigm shift within the ML community, showcasing their…

Computation and Language · Computer Science 2024-04-17 Bo Liu , Liming Zhan , Zexin Lu , Yujie Feng , Lei Xue , Xiao-Ming Wu

Metropolitan scale vehicular traffic modeling is used by a variety of private and public sector urban mobility stakeholders to inform the design and operations of road networks. High-resolution stochastic traffic simulators are increasingly…

Multiagent Systems · Computer Science 2021-09-24 Neha Arora , Yi-fan Chen , Sanjay Ganapathy , Yechen Li , Ziheng Lin , Carolina Osorio , Andrew Tomkins , Iveel Tsogsuren

The next Point of Interest (POI) recommendation task is to predict users' immediate next POI visit given their historical data. Location-Based Social Network (LBSN) data, which is often used for the next POI recommendation task, comes with…

Information Retrieval · Computer Science 2024-08-02 Peibo Li , Maarten de Rijke , Hao Xue , Shuang Ao , Yang Song , Flora D. Salim

Training Large Language Models (LLMs) typically involves a two-stage pipeline at the output layer: hidden states are projected into vocabulary logits via a linear transformation (lm_head), followed by cross-entropy loss computation against…

Machine Learning · Computer Science 2025-11-25 Jianbing Dong , Jianbin Chang

The traffic assignment problem is essential for traffic flow analysis, traditionally solved using mathematical programs under the Equilibrium principle. These methods become computationally prohibitive for large-scale networks due to…

Machine Learning · Computer Science 2026-04-28 Mostafa Ameli , Sulthana Shams , Van Anh Le , Alexander Skabardonis

Machine learning practitioners often face significant challenges in formally integrating their prior knowledge and beliefs into predictive models, limiting the potential for nuanced and context-aware analyses. Moreover, the expertise needed…

Machine Learning · Statistics 2024-12-23 James Requeima , John Bronskill , Dami Choi , Richard E. Turner , David Duvenaud

Urban computing has emerged as a multidisciplinary field that harnesses data-driven technologies to address challenges and improve urban living. Traditional approaches, while beneficial, often face challenges with generalization,…

Computers and Society · Computer Science 2025-11-11 Zhonghang Li , Lianghao Xia , Xubin Ren , Jiabin Tang , Tianyi Chen , Yong Xu , Chao Huang

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…

Object-goal navigation requires mobile robots to efficiently locate targets with visual and spatial information, yet existing methods struggle with generalization in unseen environments. Heuristic approaches with naive metrics fail in…

Robotics · Computer Science 2025-07-22 Mengying Lin , Shugao Liu , Dingxi Zhang , Yaran Chen , Zhaoran Wang , Haoran Li , Dongbin Zhao

While accurate traffic forecasting is vital for Intelligent Transportation Systems (ITS), effectively communicating predicted conditions via natural language for human-centric decision support remains a challenge and is often handled…

Machine Learning · Computer Science 2026-01-13 Zeming Du , Qitan Shao , Hongfei Liu , Yong Zhang

Understanding urban human mobility patterns at various spatial levels is essential for social science. This study presents a machine learning framework to downscale origin-destination (OD) taxi trips flows in New York City from a larger…

Machine Learning · Computer Science 2025-09-29 Yuqin Jiang , Andrey A. Popov , Tianle Duan , Qingchun Li

Large language models (LLMs) have recently demonstrated strong reasoning capabilities and attracted increasing research attention in the field of autonomous driving (AD). However, safe application of LLMs on AD perception and prediction…

Computer Vision and Pattern Recognition · Computer Science 2026-05-01 Yanjiao Liu , Jiawei Liu , Xun Gong , Zifei Nie
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