Cover Image

Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Liu, Qingxiang, Liu, Xu, Liu, Chenghao, Wen, Qingsong, Liang, Yuxuan
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Empowering Time Series Analysis with Synthetic Data: A Survey and Outlook in the Era of Foundation Models
by: Liu, Xu, et al.
Published: (2025)

OccamVTS: Distilling Vision Models to 1% Parameters for Time Series Forecasting
by: Lyu, Sisuo, et al.
Published: (2025)

Moirai-MoE: Empowering Time Series Foundation Models with Sparse Mixture of Experts
by: Liu, Xu, et al.
Published: (2024)

Discrete Prototypical Memories for Federated Time Series Foundation Models
by: Deng, Liwei, et al.
Published: (2026)

TS-Memory: Plug-and-Play Memory for Time Series Foundation Models
by: Lyu, Sisuo, et al.
Published: (2026)

RobustTSF: Towards Theory and Design of Robust Time Series Forecasting with Anomalies
by: Cheng, Hao, et al.
Published: (2024)

TwinS: Revisiting Non-Stationarity in Multivariate Time Series Forecasting
by: Hu, Jiaxi, et al.
Published: (2024)

It's TIME: Towards the Next Generation of Time Series Forecasting Benchmarks
by: Qiao, Zhongzheng, et al.
Published: (2026)

Time-SSM: Simplifying and Unifying State Space Models for Time Series Forecasting
by: Hu, Jiaxi, et al.
Published: (2024)

UniTime: A Language-Empowered Unified Model for Cross-Domain Time Series Forecasting
by: Liu, Xu, et al.
Published: (2023)

Multi-Order Wavelet Derivative Transform for Deep Time Series Forecasting
by: Zhou, Ziyu, et al.
Published: (2025)

Foundation Models for Time Series Analysis: A Tutorial and Survey
by: Liang, Yuxuan, et al.
Published: (2024)

ShapeX: Shapelet-Driven Post Hoc Explanations for Time Series Classification Models
by: Huang, Bosong, et al.
Published: (2025)

Toward Physics-guided Time Series Embedding
by: Hu, Jiaxi, et al.
Published: (2024)

Multi-Scale Finetuning for Encoder-based Time Series Foundation Models
by: Qiao, Zhongzheng, et al.
Published: (2025)

Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting
by: Zhong, Siru, et al.
Published: (2025)

Perceive, Route and Modulate: Dynamic Pattern Recalibration for Time Series Forecasting
by: Zhong, Siru, et al.
Published: (2026)

NuwaTS: a Foundation Model Mending Every Incomplete Time Series
by: Cheng, Jinguo, et al.
Published: (2024)

Achieving Time Series Reasoning Requires Rethinking Model Design, Tasks Formulation, and Evaluation
by: Kong, Yaxuan, et al.
Published: (2025)

A Survey on Diffusion Models for Time Series and Spatio-Temporal Data
by: Yang, Yiyuan, et al.
Published: (2024)

TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables
by: Wang, Yuxuan, et al.
Published: (2024)

Unlocking the Power of LSTM for Long Term Time Series Forecasting
by: Kong, Yaxuan, et al.
Published: (2024)

GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation
by: Aksu, Taha, et al.
Published: (2024)

OATS: Online Data Augmentation for Time Series Foundation Models
by: Deng, Junwei, et al.
Published: (2026)

Causal Time Series Generation via Diffusion Models
by: Xia, Yutong, et al.
Published: (2025)

Personalized Federated Learning for Spatio-Temporal Forecasting: A Dual Semantic Alignment-Based Contrastive Approach
by: Liu, Qingxiang, et al.
Published: (2024)

TSFMAudit: Data Contamination Auditing in Forecasting Time Series Foundation Models
by: Li, Hongkai, et al.
Published: (2026)

A Mamba Foundation Model for Time Series Forecasting
by: Ma, Haoyu, et al.
Published: (2024)

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

Beyond Extrapolation: Knowledge Utilization Paradigm with Bidirectional Inspiration for Time Series Forecasting
by: Chong, Liu, et al.
Published: (2026)

Abnormality Forecasting: Time Series Anomaly Prediction via Future Context Modeling
by: Zhao, Sinong, et al.
Published: (2024)

MSGNet: Learning Multi-Scale Inter-Series Correlations for Multivariate Time Series Forecasting
by: Cai, Wanlin, et al.
Published: (2023)

UniTST: Effectively Modeling Inter-Series and Intra-Series Dependencies for Multivariate Time Series Forecasting
by: Liu, Juncheng, et al.
Published: (2024)

Attractor Memory for Long-Term Time Series Forecasting: A Chaos Perspective
by: Hu, Jiaxi, et al.
Published: (2024)

Heterogeneity-Informed Meta-Parameter Learning for Spatiotemporal Time Series Forecasting
by: Dong, Zheng, et al.
Published: (2024)

DAM: Towards A Foundation Model for Time Series Forecasting
by: Darlow, Luke, et al.
Published: (2024)

Moirai 2.0: When Less Is More for Time Series Forecasting
by: Liu, Chenghao, et al.
Published: (2025)

REFOL: Resource-Efficient Federated Online Learning for Traffic Flow Forecasting
by: Liu, Qingxiang, et al.
Published: (2024)

EIDOS: Latent-Space Predictive Learning for Time Series Foundation Models
by: Zhou, Xinxing, et al.
Published: (2026)

TimeCMA: Towards LLM-Empowered Multivariate Time Series Forecasting via Cross-Modality Alignment
by: Liu, Chenxi, et al.
Published: (2024)