Adapting LLMs to Time Series Forecasting via Temporal Heterogeneity Modeling and Semantic Alignment
Fuente:
arXiv
Saved in:
| Main Authors: | Sun, Yanru, Eldele, Emadeldeen, Xie, Zongxia, Wang, Yucheng, Niu, Wenzhe, Hu, Qinghua, Kwoh, Chee Keong, Wu, Min |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Hierarchical Classification Auxiliary Network for Time Series Forecasting
by: Sun, Yanru, et al.
Published: (2024)
by: Sun, Yanru, et al.
Published: (2024)
Learning Pattern-Specific Experts for Time Series Forecasting Under Patch-level Distribution Shift
by: Sun, Yanru, et al.
Published: (2024)
by: Sun, Yanru, et al.
Published: (2024)
Label-efficient Time Series Representation Learning: A Review
by: Eldele, Emadeldeen, et al.
Published: (2023)
by: Eldele, Emadeldeen, et al.
Published: (2023)
PPGF: Probability Pattern-Guided Time Series Forecasting
by: Sun, Yanru, et al.
Published: (2025)
by: Sun, Yanru, et al.
Published: (2025)
Patch-wise Structural Loss for Time Series Forecasting
by: Kudrat, Dilfira, et al.
Published: (2025)
by: Kudrat, Dilfira, et al.
Published: (2025)
LangTime: A Language-Guided Unified Model for Time Series Forecasting with Proximal Policy Optimization
by: Niu, Wenzhe, et al.
Published: (2025)
by: Niu, Wenzhe, et al.
Published: (2025)
Lightweight Channel-wise Dynamic Fusion Model: Non-stationary Time Series Forecasting via Entropy Analysis
by: Jia, Tianyu, et al.
Published: (2025)
by: Jia, Tianyu, et al.
Published: (2025)
SEED: Spectral Entropy-Guided Evaluation of SpatialTemporal Dependencies for Multivariate Time Series Forecasting
by: Xiong, Feng, et al.
Published: (2025)
by: Xiong, Feng, et al.
Published: (2025)
TSLANet: Rethinking Transformers for Time Series Representation Learning
by: Eldele, Emadeldeen, et al.
Published: (2024)
by: Eldele, Emadeldeen, et al.
Published: (2024)
A Unified Shape-Aware Foundation Model for Time Series Classification
by: Liu, Zhen, et al.
Published: (2026)
by: Liu, Zhen, et al.
Published: (2026)
Entropy Guided Dynamic Patch Segmentation for Time Series Transformers
by: Abeywickrama, Sachith, et al.
Published: (2025)
by: Abeywickrama, Sachith, et al.
Published: (2025)
Time Series Domain Adaptation via Latent Invariant Causal Mechanism
by: Cai, Ruichu, et al.
Published: (2025)
by: Cai, Ruichu, et al.
Published: (2025)
MSA-CNN: A Lightweight Multi-Scale CNN with Attention for Sleep Stage Classification
by: Goerttler, Stephan, et al.
Published: (2025)
by: Goerttler, Stephan, et al.
Published: (2025)
Learning Soft Sparse Shapes for Efficient Time-Series Classification
by: Liu, Zhen, et al.
Published: (2025)
by: Liu, Zhen, et al.
Published: (2025)
Target-specific Adaptation and Consistent Degradation Alignment for Cross-Domain Remaining Useful Life Prediction
by: Hou, Yubo, et al.
Published: (2025)
by: Hou, Yubo, et al.
Published: (2025)
Bridging Distribution Gaps in Time Series Foundation Model Pretraining with Prototype-Guided Normalization
by: Gong, Peiliang, et al.
Published: (2025)
by: Gong, Peiliang, et al.
Published: (2025)
Evidentially Calibrated Source-Free Time-Series Domain Adaptation with Temporal Imputation
by: Ragab, Mohamed, et al.
Published: (2024)
by: Ragab, Mohamed, et al.
Published: (2024)
Evidential Domain Adaptation for Remaining Useful Life Prediction with Incomplete Degradation
by: Hou, Yubo, et al.
Published: (2026)
by: Hou, Yubo, et al.
Published: (2026)
Enhancing Time Series Forecasting via Multi-Level Text Alignment with LLMs
by: Zhao, Taibiao, et al.
Published: (2025)
by: Zhao, Taibiao, et al.
Published: (2025)
Set a Thief to Catch a Thief: Combating Label Noise through Noisy Meta Learning
by: Wang, Hanxuan, et al.
Published: (2025)
by: Wang, Hanxuan, et al.
Published: (2025)
Enhancing LLMs for Time Series Forecasting via Structure-Guided Cross-Modal Alignment
by: Sun, Siming, et al.
Published: (2025)
by: Sun, Siming, et al.
Published: (2025)
FOCUS: Frequency-Optimized Conditioning of DiffUSion Models for mitigating catastrophic forgetting during Test-Time Adaptation
by: Tjio, Gabriel, et al.
Published: (2025)
by: Tjio, Gabriel, et al.
Published: (2025)
TimeCatcher: A Variational Framework for Volatility-Aware Forecasting of Non-Stationary Time Series
by: Chen, Zhiyu, et al.
Published: (2026)
by: Chen, Zhiyu, et al.
Published: (2026)
UniFault: A Fault Diagnosis Foundation Model from Bearing Data
by: Eldele, Emadeldeen, et al.
Published: (2025)
by: Eldele, Emadeldeen, et al.
Published: (2025)
Enhancing Zero-Shot Time Series Forecasting in Off-the-Shelf LLMs via Noise Injection
by: Yin, Xingyou, et al.
Published: (2025)
by: Yin, Xingyou, et al.
Published: (2025)
Time-Prompt: Integrated Heterogeneous Prompts for Unlocking LLMs in Time Series Forecasting
by: Wang, Zesen, et al.
Published: (2025)
by: Wang, Zesen, et al.
Published: (2025)
Physics-Informed Neural Networks in Electromagnetic and Nanophotonic Design
by: Abdelraouf, Omar A. M., et al.
Published: (2025)
by: Abdelraouf, Omar A. M., et al.
Published: (2025)
Graph Generation Powered with LLMs for Boosting Multivariate Time-Series Representation Learning
by: Wang, Yucheng, et al.
Published: (2024)
by: Wang, Yucheng, et al.
Published: (2024)
Fully-Connected Spatial-Temporal Graph for Multivariate Time-Series Data
by: Wang, Yucheng, et al.
Published: (2023)
by: Wang, Yucheng, et al.
Published: (2023)
Temporal Source Recovery for Time-Series Source-Free Unsupervised Domain Adaptation
by: Wang, Yucheng, et al.
Published: (2024)
by: Wang, Yucheng, et al.
Published: (2024)
Personalized Federated Learning for Spatio-Temporal Forecasting: A Dual Semantic Alignment-Based Contrastive Approach
by: Liu, Qingxiang, et al.
Published: (2024)
by: Liu, Qingxiang, et al.
Published: (2024)
Bridging Past and Future: Distribution-Aware Alignment for Time Series Forecasting
by: Hu, Yifan, et al.
Published: (2025)
by: Hu, Yifan, et al.
Published: (2025)
Addressing Concept Shift in Online Time Series Forecasting: Detect-then-Adapt
by: Zhang, YiFan, et al.
Published: (2024)
by: Zhang, YiFan, et al.
Published: (2024)
Rethinking the Role of LLMs in Time Series Forecasting
by: Qiu, Xin, et al.
Published: (2026)
by: Qiu, Xin, et al.
Published: (2026)
TimeMosaic: Temporal Heterogeneity Guided Time Series Forecasting via Adaptive Granularity Patch and Segment-wise Decoding
by: Ding, Kuiye, et al.
Published: (2025)
by: Ding, Kuiye, et al.
Published: (2025)
Calibration of Time-Series Forecasting: Detecting and Adapting Context-Driven Distribution Shift
by: Chen, Mouxiang, et al.
Published: (2023)
by: Chen, Mouxiang, et al.
Published: (2023)
From Absolute to Relative: Rethinking Reward Shaping in Group-Based Reinforcement Learning
by: Niu, Wenzhe, et al.
Published: (2026)
by: Niu, Wenzhe, et al.
Published: (2026)
Hierarchical Multimodal LLMs with Semantic Space Alignment for Enhanced Time Series Classification
by: Tao, Xiaoyu, et al.
Published: (2024)
by: Tao, Xiaoyu, et al.
Published: (2024)
Attention as Robust Representation for Time Series Forecasting
by: Niu, PeiSong, et al.
Published: (2024)
by: Niu, PeiSong, et al.
Published: (2024)
CTRL: Continuous-Time Representation Learning on Temporal Heterogeneous Information Network
by: Li, Chenglin, et al.
Published: (2024)
by: Li, Chenglin, et al.
Published: (2024)
Similar Items
-
Hierarchical Classification Auxiliary Network for Time Series Forecasting
by: Sun, Yanru, et al.
Published: (2024) -
Learning Pattern-Specific Experts for Time Series Forecasting Under Patch-level Distribution Shift
by: Sun, Yanru, et al.
Published: (2024) -
Label-efficient Time Series Representation Learning: A Review
by: Eldele, Emadeldeen, et al.
Published: (2023) -
PPGF: Probability Pattern-Guided Time Series Forecasting
by: Sun, Yanru, et al.
Published: (2025) -
Patch-wise Structural Loss for Time Series Forecasting
by: Kudrat, Dilfira, et al.
Published: (2025)