Spectral-Aware Text-to-Time Series Generation with Billion-Scale Multimodal Meteorological Data
Fuente:
arXiv
Saved in:
| Main Author: | Zhang, Shijie |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
TimeHF: Billion-Scale Time Series Models Guided by Human Feedback
by: Qi, Yongzhi, et al.
Published: (2025)
by: Qi, Yongzhi, et al.
Published: (2025)
Spectral Text Fusion: A Frequency-Aware Approach to Multimodal Time-Series Forecasting
by: Nguyen, Huu Hiep, et al.
Published: (2026)
by: Nguyen, Huu Hiep, et al.
Published: (2026)
Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts
by: Shi, Xiaoming, et al.
Published: (2024)
by: Shi, Xiaoming, et al.
Published: (2024)
Scaling Structure Aware Virtual Screening to Billions of Molecules with SPRINT
by: McNutt, Andrew T., et al.
Published: (2024)
by: McNutt, Andrew T., et al.
Published: (2024)
Billion-Scale Graph Foundation Models
by: Bechler-Speicher, Maya, et al.
Published: (2026)
by: Bechler-Speicher, Maya, et al.
Published: (2026)
Empowering Time Series Analysis with Large-Scale Multimodal Pretraining
by: Chen, Peng, et al.
Published: (2026)
by: Chen, Peng, et al.
Published: (2026)
Dual-Forecaster: A Multimodal Time Series Model Integrating Descriptive and Predictive Texts
by: Wu, Wenfa, et al.
Published: (2025)
by: Wu, Wenfa, et al.
Published: (2025)
Domain-Independent Automatic Generation of Descriptive Texts for Time-Series Data
by: Dohi, Kota, et al.
Published: (2024)
by: Dohi, Kota, et al.
Published: (2024)
Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting
by: Yao, Yueyang, et al.
Published: (2025)
by: Yao, Yueyang, et al.
Published: (2025)
OpenTSLM: Time-Series Language Models for Reasoning over Multivariate Medical Text- and Time-Series Data
by: Langer, Patrick, et al.
Published: (2025)
by: Langer, Patrick, et al.
Published: (2025)
Aurora: Towards Universal Generative Multimodal Time Series Forecasting
by: Wu, Xingjian, et al.
Published: (2025)
by: Wu, Xingjian, et al.
Published: (2025)
Fortifying Time Series: DTW-Certified Robust Anomaly Detection
by: Liu, Shijie, et al.
Published: (2026)
by: Liu, Shijie, et al.
Published: (2026)
Zenith: Scaling up Ranking Models for Billion-scale Livestreaming Recommendation
by: Zhang, Ruifeng, et al.
Published: (2026)
by: Zhang, Ruifeng, et al.
Published: (2026)
Population Aware Diffusion for Time Series Generation
by: Li, Yang, et al.
Published: (2025)
by: Li, Yang, et al.
Published: (2025)
Time Scale Network: A Shallow Neural Network For Time Series Data
by: Meyer, Trevor, et al.
Published: (2023)
by: Meyer, Trevor, et al.
Published: (2023)
PA-RNet: Perturbation-Aware Residual Network for Robust Multimodal Time Series Forecasting
by: Zhu, Enqiang, et al.
Published: (2025)
by: Zhu, Enqiang, et al.
Published: (2025)
BoundAD: Boundary-Aware Negative Generation for Time Series Anomaly Detection
by: Wang, Xiancheng, et al.
Published: (2026)
by: Wang, Xiancheng, et al.
Published: (2026)
CGSTA: Cross-Scale Graph Contrast with Stability-Aware Alignment for Multivariate Time-Series Anomaly Detection
by: Qi, Zhongpeng, et al.
Published: (2026)
by: Qi, Zhongpeng, et al.
Published: (2026)
TimeMar: Multi-Scale Autoregressive Modeling for Unconditional Time Series Generation
by: Xu, Xiangyu, et al.
Published: (2026)
by: Xu, Xiangyu, et al.
Published: (2026)
Synthetic Series-Symbol Data Generation for Time Series Foundation Models
by: Wang, Wenxuan, et al.
Published: (2025)
by: Wang, Wenxuan, et al.
Published: (2025)
Macro Graph of Experts for Billion-Scale Multi-Task Recommendation
by: Yao, Hongyu, et al.
Published: (2025)
by: Yao, Hongyu, et al.
Published: (2025)
T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models
by: Ge, Yunfeng, et al.
Published: (2025)
by: Ge, Yunfeng, et al.
Published: (2025)
A Review on Generative AI Models for Synthetic Medical Text, Time Series, and Longitudinal Data
by: Loni, Mohammad, et al.
Published: (2024)
by: Loni, Mohammad, et al.
Published: (2024)
Conv-like Scale-Fusion Time Series Transformer: A Multi-Scale Representation for Variable-Length Long Time Series
by: Zhang, Kai, et al.
Published: (2025)
by: Zhang, Kai, et al.
Published: (2025)
MedualTime: A Dual-Adapter Language Model for Medical Time Series-Text Multimodal Learning
by: Ye, Jiexia, et al.
Published: (2024)
by: Ye, Jiexia, et al.
Published: (2024)
Each Prompt Matters: Scaling Reinforcement Learning Without Wasting Rollouts on Hundred-Billion-Scale MoE
by: Zeng, Anxiang, et al.
Published: (2025)
by: Zeng, Anxiang, et al.
Published: (2025)
FAIM: Frequency-Aware Interactive Mamba for Time Series Classification
by: Zhang, Da, et al.
Published: (2025)
by: Zhang, Da, et al.
Published: (2025)
BioFormer: Rethinking Cross-Subject Generalization via Spectral Structural Alignment in Biomedical Time-Series
by: Du, Guikang, et al.
Published: (2026)
by: Du, Guikang, et al.
Published: (2026)
Scaling Law for Large-Scale Pre-Training Using Chaotic Time Series and Predictability in Financial Time Series
by: Takemoto, Yuki
Published: (2025)
by: Takemoto, Yuki
Published: (2025)
Mitigating Data Scarcity in Time Series Analysis: A Foundation Model with Series-Symbol Data Generation
by: Wang, Wenxuan, et al.
Published: (2025)
by: Wang, Wenxuan, et al.
Published: (2025)
ChatTime: A Unified Multimodal Time Series Foundation Model Bridging Numerical and Textual Data
by: Wang, Chengsen, et al.
Published: (2024)
by: Wang, Chengsen, et al.
Published: (2024)
Generating Synthetic Time Series Data for Cyber-Physical Systems
by: Sommers, Alexander, et al.
Published: (2024)
by: Sommers, Alexander, et al.
Published: (2024)
DiTS: Multimodal Diffusion Transformers Are Time Series Forecasters
by: Zhang, Haoran, et al.
Published: (2026)
by: Zhang, Haoran, et al.
Published: (2026)
Towards Stable and Structured Time Series Generation with Perturbation-Aware Flow Matching
by: Zhang, Jintao, et al.
Published: (2025)
by: Zhang, Jintao, et al.
Published: (2025)
LipNeXt: Scaling up Lipschitz-based Certified Robustness to Billion-parameter Models
by: Hu, Kai, et al.
Published: (2026)
by: Hu, Kai, et al.
Published: (2026)
CLIPTime: Time-Aware Multimodal Representation Learning from Images and Text
by: Rani, Anju, et al.
Published: (2025)
by: Rani, Anju, et al.
Published: (2025)
ProtoTS: Learning Hierarchical Prototypes for Explainable Time Series Forecasting
by: Peng, Ziheng, et al.
Published: (2025)
by: Peng, Ziheng, et al.
Published: (2025)
Scaling Recurrent Neural Networks to a Billion Parameters with Zero-Order Optimization
by: Chaubard, Francois, et al.
Published: (2025)
by: Chaubard, Francois, et al.
Published: (2025)
A Generalized Spectral Framework to Expain Neural Scaling and Compression Dynamics
by: Zhang, Yizhou
Published: (2025)
by: Zhang, Yizhou
Published: (2025)
FreIE: Low-Frequency Spectral Bias in Neural Networks for Time-Series Tasks
by: Sun, Jialong, et al.
Published: (2025)
by: Sun, Jialong, et al.
Published: (2025)
Similar Items
-
TimeHF: Billion-Scale Time Series Models Guided by Human Feedback
by: Qi, Yongzhi, et al.
Published: (2025) -
Spectral Text Fusion: A Frequency-Aware Approach to Multimodal Time-Series Forecasting
by: Nguyen, Huu Hiep, et al.
Published: (2026) -
Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts
by: Shi, Xiaoming, et al.
Published: (2024) -
Scaling Structure Aware Virtual Screening to Billions of Molecules with SPRINT
by: McNutt, Andrew T., et al.
Published: (2024) -
Billion-Scale Graph Foundation Models
by: Bechler-Speicher, Maya, et al.
Published: (2026)