Cover Image

Breaking the Context Bottleneck on Long Time Series Forecasting

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ma, Chao, Hou, Yikai, Li, Xiang, Sun, Yinggang, Yu, Haining, Fang, Zhou, Qu, Jiaxing
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Long Input Sequence Network for Long Time Series Forecasting
by: Ma, Chao, et al.
Published: (2024)

ISMRNN: An Implicitly Segmented RNN Method with Mamba for Long-Term Time Series Forecasting
by: Zhao, GaoXiang, et al.
Published: (2024)

DDTime: Dataset Distillation with Spectral Alignment and Information Bottleneck for Time-Series Forecasting
by: Li, Yuqi, et al.
Published: (2025)

Nested Spatio-Temporal Time Series Forecasting
by: Ai, Yinghao, et al.
Published: (2026)

DMamba: Decomposition-enhanced Mamba for Time Series Forecasting
by: Chen, Ruxuan, et al.
Published: (2026)

Why Do Transformers Fail to Forecast Time Series In-Context?
by: Zhou, Yufa, et al.
Published: (2025)

To See Far, Look Close: Evolutionary Forecasting for Long-term Time Series
by: Ma, Jiaming, et al.
Published: (2026)

Scaling Law for Time Series Forecasting
by: Shi, Jingzhe, et al.
Published: (2024)

Glocal Information Bottleneck for Time Series Imputation
by: Yang, Jie, et al.
Published: (2025)

Calibration of Time-Series Forecasting: Detecting and Adapting Context-Driven Distribution Shift
by: Chen, Mouxiang, et al.
Published: (2023)

DySCo: Dynamic Semantic Compression for Effective Long-term Time Series Forecasting
by: Ao, Xiang, et al.
Published: (2026)

Quantum Kernel-Based Long Short-term Memory for Climate Time-Series Forecasting
by: Hsu, Yu-Chao, et al.
Published: (2024)

SDMixer: Sparse Dual-Mixer for Time Series Forecasting
by: Ao, Xiang
Published: (2026)

Revisiting Long-term Time Series Forecasting: An Investigation on Linear Mapping
by: Li, Zhe, et al.
Published: (2023)

PENGUIN: Enhancing Transformer with Periodic-Nested Group Attention for Long-term Time Series Forecasting
by: Sun, Tian, et al.
Published: (2025)

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting
by: Liu, Zhining, et al.
Published: (2025)

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

Attention as Robust Representation for Time Series Forecasting
by: Niu, PeiSong, et al.
Published: (2024)

There are no Champions in Supervised Long-Term Time Series Forecasting
by: Brigato, Lorenzo, et al.
Published: (2025)

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting
by: Yao, Yueyang, et al.
Published: (2025)

Context Matters: Leveraging Contextual Features for Time Series Forecasting
by: Chattopadhyay, Sameep, et al.
Published: (2024)

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

Sparse-VQ Transformer: An FFN-Free Framework with Vector Quantization for Enhanced Time Series Forecasting
by: Zhao, Yanjun, et al.
Published: (2024)

Breaking the Exploration Bottleneck: Rubric-Scaffolded Reinforcement Learning for General LLM Reasoning
by: Zhou, Yang, et al.
Published: (2025)

Baguan-TS: A Sequence-Native In-Context Learning Model for Time Series Forecasting with Covariates
by: Yang, Linxiao, et al.
Published: (2026)

Dynamic Long-Term Time-Series Forecasting via Meta Transformer Networks
by: Ma'sum, Muhammad Anwar, et al.
Published: (2024)

TimeX++: Learning Time-Series Explanations with Information Bottleneck
by: Liu, Zichuan, et al.
Published: (2024)

Mixture-of-Linear-Experts for Long-term Time Series Forecasting
by: Ni, Ronghao, et al.
Published: (2023)

Wavelet Mixture of Experts for Time Series Forecasting
by: Zhou, Zheng, et al.
Published: (2025)

Dual-Prototype Disentanglement: A Context-Aware Enhancement Framework for Time Series Forecasting
by: Yang, Haonan, et al.
Published: (2026)

DPWMixer: Dual-Path Wavelet Mixer for Long-Term Time Series Forecasting
by: Qianyang, Li, et al.
Published: (2025)

TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting
by: Wang, Shiyu, et al.
Published: (2024)

Disentangling Long-Short Term State Under Unknown Interventions for Online Time Series Forecasting
by: Cai, Ruichu, et al.
Published: (2025)

Multi-Scale Dilated Convolution Network for Long-Term Time Series Forecasting
by: Li, Feifei, et al.
Published: (2024)

BEAT: Balanced Frequency Adaptive Tuning for Long-Term Time-Series Forecasting
by: Li, Zhixuan, et al.
Published: (2025)

Disentangled Parameter-Efficient Linear Model for Long-Term Time Series Forecasting
by: Zhao, Yuang, et al.
Published: (2024)

SageFormer: Series-Aware Framework for Long-term Multivariate Time Series Forecasting
by: Zhang, Zhenwei, et al.
Published: (2023)

PeriodNet: Boosting the Potential of Attention Mechanism for Time Series Forecasting
by: Zhao, Bowen, et al.
Published: (2025)

Capture Timing-Attention of Events in Clinical Time Series
by: Li, Jia, et al.
Published: (2026)

TimelyGPT: Extrapolatable Transformer Pre-training for Long-term Time-Series Forecasting in Healthcare
by: Song, Ziyang, et al.
Published: (2023)