Logo-LLM: Local and Global Modeling with Large Language Models for Time Series Forecasting

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Ou, Wenjie, Zhao, Zhishuo, Chen, Cheng, Guo, Dongyue, Lin, Yi
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

WinNet: Make Only One Convolutional Layer Effective for Time Series Forecasting
por: Ou, Wenjie, et al.
Publicado: (2023)

LogoRA: Local-Global Representation Alignment for Robust Time Series Classification
por: Zhang, Huanyu, et al.
Publicado: (2024)

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

T-LLM: Teaching Large Language Models to Forecast Time Series via Temporal Distillation
por: Guo, Suhan, et al.
Publicado: (2026)

LoFT-LLM: Low-Frequency Time-Series Forecasting with Large Language Models
por: You, Jiacheng, et al.
Publicado: (2025)

Hierarchical Classification Auxiliary Network for Time Series Forecasting
por: Sun, Yanru, et al.
Publicado: (2024)

LLM-PS: Empowering Large Language Models for Time Series Forecasting with Temporal Patterns and Semantics
por: Tang, Jialiang, et al.
Publicado: (2025)

AutoTimes: Autoregressive Time Series Forecasters via Large Language Models
por: Liu, Yong, et al.
Publicado: (2024)

CC-Time: Cross-Model and Cross-Modality Time Series Forecasting
por: Chen, Peng, et al.
Publicado: (2025)

Large Language Models Are Zero-Shot Time Series Forecasters
por: Gruver, Nate, et al.
Publicado: (2023)

FRWKV:Frequency-Domain Linear Attention for Long-Term Time Series Forecasting
por: Yang, Qingyuan, et al.
Publicado: (2025)

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

SPAT: Sensitivity-based Multihead-attention Pruning on Time Series Forecasting Models
por: Guo, Suhan, et al.
Publicado: (2025)

Position: Beyond Model-Centric Prediction -- Agentic Time Series Forecasting
por: Cheng, Mingyue, et al.
Publicado: (2026)

Multi-Modal View Enhanced Large Vision Models for Long-Term Time Series Forecasting
por: Shen, ChengAo, et al.
Publicado: (2025)

Gaussian Process Latent Variable Modeling for Few-shot Time Series Forecasting
por: Cheng, Yunyao, et al.
Publicado: (2022)

Local vs. Global Models for Hierarchical Forecasting
por: Yingjie, Zhao, et al.
Publicado: (2024)

Efficient Multivariate Time Series Forecasting via Calibrated Language Models with Privileged Knowledge Distillation
por: Liu, Chenxi, et al.
Publicado: (2025)

Learning Pattern-Specific Experts for Time Series Forecasting Under Patch-level Distribution Shift
por: Sun, Yanru, et al.
Publicado: (2024)

FRWKV+: Adaptive Periodic-Position Branch Interaction for Frequency-Space Linear Time Series Forecasting
por: Yang, Qingyuan, et al.
Publicado: (2026)

STELLA: Guiding Large Language Models for Time Series Forecasting with Semantic Abstractions
por: Fan, Junjie, et al.
Publicado: (2025)

WFTNet: Exploiting Global and Local Periodicity in Long-term Time Series Forecasting
por: Liu, Peiyuan, et al.
Publicado: (2023)

SEMPO: Lightweight Foundation Models for Time Series Forecasting
por: He, Hui, et al.
Publicado: (2025)

Multi-variable Adversarial Time-Series Forecast Model
por: Chen, Xiaoqiao
Publicado: (2024)

Apollo-Forecast: Overcoming Aliasing and Inference Speed Challenges in Language Models for Time Series Forecasting
por: Yin, Tianyi, et al.
Publicado: (2024)

TriP-LLM: A Tri-Branch Patch-wise Large Language Model Framework for Time-Series Anomaly Detection
por: Yu, Yuan-Cheng, et al.
Publicado: (2025)

Semantic-Enhanced Time-Series Forecasting via Large Language Models
por: Liu, Hao, et al.
Publicado: (2025)

Adversarial Vulnerabilities in Large Language Models for Time Series Forecasting
por: Liu, Fuqiang, et al.
Publicado: (2024)

TimeGPT in Load Forecasting: A Large Time Series Model Perspective
por: Liao, Wenlong, et al.
Publicado: (2024)

FLAME: Flow Enhanced Legendre Memory Models for General Time Series Forecasting
por: Wu, Xingjian, et al.
Publicado: (2025)

Efficient Model Selection for Time Series Forecasting via LLMs
por: Wei, Wang, et al.
Publicado: (2025)

DisenTS: Disentangled Channel Evolving Pattern Modeling for Multivariate Time Series Forecasting
por: Liu, Zhiding, et al.
Publicado: (2024)

SparseTSF: Modeling Long-term Time Series Forecasting with 1k Parameters
por: Lin, Shengsheng, et al.
Publicado: (2024)

Are Language Models Actually Useful for Time Series Forecasting?
por: Tan, Mingtian, et al.
Publicado: (2024)

LLM-Integrated Bayesian State Space Models for Multimodal Time-Series Forecasting
por: Cho, Sungjun, et al.
Publicado: (2025)

LightGTS: A Lightweight General Time Series Forecasting Model
por: Wang, Yihang, et al.
Publicado: (2025)

LTSM-Bundle: A Toolbox and Benchmark on Large Language Models for Time Series Forecasting
por: Chuang, Yu-Neng, et al.
Publicado: (2024)

Towards a General Time Series Forecasting Model with Unified Representation and Adaptive Transfer
por: Wang, Yihang, et al.
Publicado: (2024)

The Rise of Diffusion Models in Time-Series Forecasting
por: Meijer, Caspar, et al.
Publicado: (2024)

TSFM-Bench: A Comprehensive and Unified Benchmark of Foundation Models for Time Series Forecasting
por: Li, Zhe, et al.
Publicado: (2024)