:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Cheng, Mingyue, Tao, Xiaoyu, Zhang, Huajian, Liu, Qi, Chen, Enhong
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence
Online Access:	https://arxiv.org/abs/2601.14968
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Can Slow-thinking LLMs Reason Over Time? Empirical Studies in Time Series Forecasting
by: Cheng, Mingyue, et al.
Published: (2025)

CastFlow: Learning Role-Specialized Agentic Workflows for Time Series Forecasting
by: Pan, Bokai, et al.
Published: (2026)

Hierarchical Multimodal LLMs with Semantic Space Alignment for Enhanced Time Series Classification
by: Tao, Xiaoyu, et al.
Published: (2024)

Time Series Forecasting as Reasoning: A Slow-Thinking Approach with Reinforced LLMs
by: Zhou, Yitong, et al.
Published: (2025)

STaR: Towards Effective and Stable Table Reasoning via Slow-Thinking Large Language Models
by: Zhang, Huajian, et al.
Published: (2025)

PiXTime: A Model for Federated Time Series Forecasting with Heterogeneous Data across Nodes
by: Zhou, Yiming, et al.
Published: (2026)

MemCast: Memory-Driven Time Series Forecasting with Experience-Conditioned Reasoning
by: Tao, Xiaoyu, et al.
Published: (2026)

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

TableTime: Reformulating Time Series Classification as Training-Free Table Understanding with Large Language Models
by: Wang, Jiahao, et al.
Published: (2024)

From Values to Tokens: An LLM-Driven Framework for Context-aware Time Series Forecasting via Symbolic Discretization
by: Tao, Xiaoyu, et al.
Published: (2025)

TimeMAE: Self-Supervised Representations of Time Series with Decoupled Masked Autoencoders
by: Cheng, Mingyue, et al.
Published: (2023)

Advancing Time Series Classification with Multimodal Language Modeling
by: Cheng, Mingyue, et al.
Published: (2024)

GeoDecider: A Coarse-to-Fine Agentic Workflow for Explainable Lithology Classification
by: Wang, Jiahao, et al.
Published: (2026)

Towards Stable and Structured Time Series Generation with Perturbation-Aware Flow Matching
by: Zhang, Jintao, et al.
Published: (2025)

StaTS: Spectral Trajectory Schedule Learning for Adaptive Time Series Forecasting with Frequency Guided Denoiser
by: Zhang, Jintao, et al.
Published: (2026)

OneCast: Structured Decomposition and Modular Generation for Cross-Domain Time Series Forecasting
by: Pan, Tingyue, et al.
Published: (2025)

AlphaCast: A Human Wisdom-LLM Intelligence Co-Reasoning Framework for Interactive Time Series Forecasting
by: Zhang, Xiaohan, et al.
Published: (2025)

Cross-Domain Pre-training with Language Models for Transferable Time Series Representations
by: Cheng, Mingyue, et al.
Published: (2024)

CAFO: Feature-Centric Explanation on Time Series Classification
by: Kim, Jaeho, et al.
Published: (2024)

Global Feature Enhancing and Fusion Framework for Strain Gauge Time Series Classification
by: Zhang, Xu, et al.
Published: (2025)

Unlocking the Potential of Large Language Models for Explainable Recommendations
by: Luo, Yucong, et al.
Published: (2023)

Continuity and Ordinality Matter: Constraining Time Series Tokens for Effective Time Series Analysis with Large Language Models
by: Li, Musheng, et al.
Published: (2026)

Synthetic Series-Symbol Data Generation for Time Series Foundation Models
by: Wang, Wenxuan, et al.
Published: (2025)

Improving Time Series Forecasting via Instance-aware Post-hoc Revision
by: Liu, Zhiding, et al.
Published: (2025)

TSINR: Capturing Temporal Continuity via Implicit Neural Representations for Time Series Anomaly Detection
by: Li, Mengxuan, et al.
Published: (2024)

TimeFlow: Towards Stochastic-Aware and Efficient Time Series Generation via Flow Matching Modeling
by: Panjing, He, et al.
Published: (2025)

Bridging Classification and Reconstruction: Cooperative Time Series Anomaly Detection
by: Tang, Qideng, et al.
Published: (2026)

ERIS: An Energy-Guided Feature Disentanglement Framework for Out-of-Distribution Time Series Classification
by: Wu, Xin, et al.
Published: (2025)

TimeMaster: Training Time-Series Multimodal LLMs to Reason via Reinforcement Learning
by: Zhang, Junru, et al.
Published: (2025)

Time Series Continuous Modeling for Imputation and Forecasting with Implicit Neural Representations
by: Naour, Etienne Le, et al.
Published: (2023)

A Unified Frequency Domain Decomposition Framework for Interpretable and Robust Time Series Forecasting
by: He, Cheng, et al.
Published: (2025)

Mitigating Data Scarcity in Time Series Analysis: A Foundation Model with Series-Symbol Data Generation
by: Wang, Wenxuan, et al.
Published: (2025)

TimeCAP: Learning to Contextualize, Augment, and Predict Time Series Events with Large Language Model Agents
by: Lee, Geon, et al.
Published: (2025)

CATS-Linear: Classification Auxiliary Linear Model for Time Series Forecasting
by: Jibao, Zipo, et al.
Published: (2025)

Gradient-based Model Shortcut Detection for Time Series Classification
by: Ibarra, Salomon, et al.
Published: (2025)

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

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

MedualTime: A Dual-Adapter Language Model for Medical Time Series-Text Multimodal Learning
by: Ye, Jiexia, et al.
Published: (2024)

A Unified Contrastive-Generative Framework for Time Series Classification
by: Liu, Ziyu, et al.
Published: (2025)

Guidelines for Augmentation Selection in Contrastive Learning for Time Series Classification
by: Liu, Ziyu, et al.
Published: (2024)