Compositional Spectral Prompts for LLM-based Online Time Series Forecasting
cs.LG
Submitted: 2026-09-02
Updated: 2026-09-02
Code: https://github.com/seungyoon-Choi/CoSPOT
Terminology
Sources
- Chronos-2: From Univariate to Universal Forecasting
- A decoder-only foundation model for time-series forecasting
- An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
- Time-LLM: Time Series Forecasting by Reprogramming Large Language Models
- iTransformer: Inverted Transformers Are Effective for Time Series Forecasting
- A Time Series is Worth 64 Words: Long-term Forecasting with Transformers
- Learning Fast and Slow for Online Time Series Forecasting
- LLaMA: Open and Efficient Foundation Language Models
- TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting
- TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis
- FITS: Modeling Time Series with $10k$ Parameters
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