:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Qiao, Zhongzheng, Pan, Sheng, Wang, Anni, Zhukova, Viktoriya, Liu, Yong, Jiang, Xudong, Wen, Qingsong, Long, Mingsheng, Jin, Ming, Liu, Chenghao
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2602.12147
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting
by: Liu, Qingxiang, et al.
Published: (2024)

Class-incremental Learning for Time Series: Benchmark and Evaluation
by: Qiao, Zhongzheng, et al.
Published: (2024)

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

Timer-XL: Long-Context Transformers for Unified Time Series Forecasting
by: Liu, Yong, et al.
Published: (2024)

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

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

DiTS: Multimodal Diffusion Transformers Are Time Series Forecasters
by: Zhang, Haoran, et al.
Published: (2026)

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

iTransformer: Inverted Transformers Are Effective for Time Series Forecasting
by: Liu, Yong, et al.
Published: (2023)

Towards Expressive Spectral-Temporal Graph Neural Networks for Time Series Forecasting
by: Jin, Ming, et al.
Published: (2023)

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

Deep Time Series Models: A Comprehensive Survey and Benchmark
by: Wang, Yuxuan, et al.
Published: (2024)

LeapTS: Rethinking Time Series Forecasting as Adaptive Multi-Horizon Scheduling
by: Pan, Sheng, et al.
Published: (2026)

Parallel Complex Diffusion for Scalable Time Series Generation
by: Cai, Rongyao, et al.
Published: (2026)

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)

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

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

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

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

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

A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection
by: Jin, Ming, et al.
Published: (2023)

Toto 2.0: Time Series Forecasting Enters the Scaling Era
by: Khwaja, Emaad, et al.
Published: (2026)

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

Quadratic Direct Forecast for Training Multi-Step Time-Series Forecast Models
by: Wang, Hao, et al.
Published: (2025)

Metadata Matters for Time Series: Informative Forecasting with Transformers
by: Dong, Jiaxiang, et al.
Published: (2024)

From Entanglement to Alignment: Representation Space Decomposition for Unsupervised Time Series Domain Adaptation
by: Cai, Rongyao, et al.
Published: (2025)

Time Evidence Fusion Network: Multi-source View in Long-Term Time Series Forecasting
by: Zhan, Tianxiang, et al.
Published: (2024)

CARD: Channel Aligned Robust Blend Transformer for Time Series Forecasting
by: Xue, Wang, et al.
Published: (2023)

TimesBERT: A BERT-Style Foundation Model for Time Series Understanding
by: Zhang, Haoran, et al.
Published: (2025)

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

HiMTM: Hierarchical Multi-Scale Masked Time Series Modeling with Self-Distillation for Long-Term Forecasting
by: Zhao, Shubao, et al.
Published: (2024)

Exploring Accuracy Law for Deep Time Series Forecasters: An Empirical Study
by: Wang, Yuxuan, et al.
Published: (2025)

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

Timer: Generative Pre-trained Transformers Are Large Time Series Models
by: Liu, Yong, et al.
Published: (2024)

Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects
by: Zhang, Kexin, et al.
Published: (2023)

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

The Procrustean Bed of Time Series: The Optimization Bias in Point-wise Loss Functions
by: Cai, Rongyao, et al.
Published: (2025)

AION: Next-Generation Tasks and Practical Harness for Time Series
by: Zhan, Tianxiang, et al.
Published: (2026)