Copertina

Embracing Large Language Models in Traffic Flow Forecasting

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Zhao, Yusheng, Luo, Xiao, Wen, Haomin, Xiao, Zhiping, Ju, Wei, Zhang, Ming
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

COOL: A Conjoint Perspective on Spatio-Temporal Graph Neural Network for Traffic Forecasting
di: Ju, Wei, et al.
Pubblicazione: (2024)

GALA: Graph Diffusion-based Alignment with Jigsaw for Source-free Domain Adaptation
di: Luo, Junyu, et al.
Pubblicazione: (2024)

Local Truncation Error-Guided Neural ODEs for Large Scale Traffic Forecasting
di: Zhang, Xiao, et al.
Pubblicazione: (2026)

Dynamic Bundling with Large Language Models for Zero-Shot Inference on Text-Attributed Graphs
di: Zhao, Yusheng, et al.
Pubblicazione: (2025)

Rank and Align: Towards Effective Source-free Graph Domain Adaptation
di: Luo, Junyu, et al.
Pubblicazione: (2024)

Towards Explainable Traffic Flow Prediction with Large Language Models
di: Guo, Xusen, et al.
Pubblicazione: (2024)

FaST: Efficient and Effective Long-Horizon Forecasting for Large-Scale Spatial-Temporal Graphs via Mixture-of-Experts
di: Zhao, Yiji, et al.
Pubblicazione: (2026)

ClimateLLM: Efficient Weather Forecasting via Frequency-Aware Large Language Models
di: Li, Shixuan, et al.
Pubblicazione: (2025)

Semi-supervised Fine-tuning for Large Language Models
di: Luo, Junyu, et al.
Pubblicazione: (2024)

Fast Inference of Removal-Based Node Influence
di: Li, Weikai, et al.
Pubblicazione: (2024)

A Survey of Data-Efficient Graph Learning
di: Ju, Wei, et al.
Pubblicazione: (2024)

Spatio-Temporal Partial Sensing Forecast for Long-term Traffic
di: Liu, Zibo, et al.
Pubblicazione: (2024)

Efficient Prompt Learning for Traffic Forecasting
di: Zhang, Qianru, et al.
Pubblicazione: (2026)

Wireless Traffic Prediction with Large Language Model
di: Zhang, Chuanting, et al.
Pubblicazione: (2025)

Rethinking Traffic Flow Forecasting: From Transition to Generatation
di: Shijiao, Li, et al.
Pubblicazione: (2025)

SVTime: Small Time Series Forecasting Models Informed by "Physics" of Large Vision Model Forecasters
di: Shen, ChengAo, et al.
Pubblicazione: (2025)

Large Language Models for Forecasting and Anomaly Detection: A Systematic Literature Review
di: Su, Jing, et al.
Pubblicazione: (2024)

Time-LLM: Time Series Forecasting by Reprogramming Large Language Models
di: Jin, Ming, et al.
Pubblicazione: (2023)

PIMCST: Physics-Informed Multi-Phase Consensus and Spatio-Temporal Few-Shot Learning for Traffic Flow Forecasting
di: Fofanah, Abdul Joseph, et al.
Pubblicazione: (2026)

A Comprehensive Survey on Deep Graph Representation Learning
di: Ju, Wei, et al.
Pubblicazione: (2023)

Revealing the Power of Masked Autoencoders in Traffic Forecasting
di: Sun, Jiarui, et al.
Pubblicazione: (2023)

FoMo-0D: A Foundation Model for Zero-shot Tabular Outlier Detection
di: Shen, Yuchen, et al.
Pubblicazione: (2024)

Spatiotemporal-aware Trend-Seasonality Decomposition Network for Traffic Flow Forecasting
di: Cao, Lingxiao, et al.
Pubblicazione: (2025)

Test-Time Learning for Large Language Models
di: Hu, Jinwu, et al.
Pubblicazione: (2025)

ST-RetNet: A Long-term Spatial-Temporal Traffic Flow Prediction Method
di: Long, Baichao, et al.
Pubblicazione: (2024)

A Hybrid Model for Traffic Incident Detection based on Generative Adversarial Networks and Transformer Model
di: Lu, Xinying, et al.
Pubblicazione: (2024)

Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting
di: Lin, Zhenan, et al.
Pubblicazione: (2025)

Hypergraph-enhanced Dual Semi-supervised Graph Classification
di: Ju, Wei, et al.
Pubblicazione: (2024)

Towards Universal Large-Scale Foundational Model for Natural Gas Demand Forecasting
di: Zhou, Xinxing, et al.
Pubblicazione: (2024)

HALO: Hierarchical Reinforcement Learning for Large-Scale Adaptive Traffic Signal Control
di: Zhu, Yaqiao, et al.
Pubblicazione: (2025)

Online Test-Time Adaptation of Spatial-Temporal Traffic Flow Forecasting
di: Guo, Pengxin, et al.
Pubblicazione: (2024)

Deep Reinforcement Learning for Traffic Light Control in Intelligent Transportation Systems
di: Zhu, Ming, et al.
Pubblicazione: (2023)

Generalising Traffic Forecasting to Regions without Traffic Observations
di: Su, Xinyu, et al.
Pubblicazione: (2025)

Efficient Traffic Forecasting on Large-Scale Road Network by Regularized Adaptive Graph Convolution
di: Wu, Kaiqi, et al.
Pubblicazione: (2025)

STGAtt: A Spatial-Temporal Unified Graph Attention Network for Traffic Flow Forecasting
di: Liang, Zhuding, et al.
Pubblicazione: (2025)

Cross-Domain Diffusion with Progressive Alignment for Efficient Adaptive Retrieval
di: Luo, Junyu, et al.
Pubblicazione: (2025)

T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models
di: Ge, Yunfeng, et al.
Pubblicazione: (2025)

Unveiling the Inflexibility of Adaptive Embedding in Traffic Forecasting
di: Wang, Hongjun, et al.
Pubblicazione: (2024)

Exploring Large Language Models for Climate Forecasting
di: Wang, Yang, et al.
Pubblicazione: (2024)

The Role of Diversity in In-Context Learning for Large Language Models
di: Xiao, Wenyang, et al.
Pubblicazione: (2025)