Pre-trained Forecasting Models: Strong Zero-Shot Feature Extractors for Time Series Classification
Fuente:
arXiv
Saved in:
| Main Authors: | Auer, Andreas, Klotz, Daniel, Böck, Sebastinan, Hochreiter, Sepp |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
TiRex: Zero-Shot Forecasting Across Long and Short Horizons with Enhanced In-Context Learning
by: Auer, Andreas, et al.
Published: (2025)
by: Auer, Andreas, et al.
Published: (2025)
Simplified priors for Object-Centric Learning
by: Patil, Vihang, et al.
Published: (2024)
by: Patil, Vihang, et al.
Published: (2024)
Zero-Shot Time Series Forecasting with Covariates via In-Context Learning
by: Auer, Andreas, et al.
Published: (2025)
by: Auer, Andreas, et al.
Published: (2025)
xLSTM Scaling Laws: Competitive Performance with Linear Time-Complexity
by: Beck, Maximilian, et al.
Published: (2025)
by: Beck, Maximilian, et al.
Published: (2025)
Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series
by: Ekambaram, Vijay, et al.
Published: (2024)
by: Ekambaram, Vijay, et al.
Published: (2024)
Energy-based Hopfield Boosting for Out-of-Distribution Detection
by: Hofmann, Claus, et al.
Published: (2024)
by: Hofmann, Claus, et al.
Published: (2024)
AP-OOD: Attention Pooling for Out-of-Distribution Detection
by: Hofmann, Claus, et al.
Published: (2026)
by: Hofmann, Claus, et al.
Published: (2026)
Indiscriminate Data Poisoning Attacks on Pre-trained Feature Extractors
by: Lu, Yiwei, et al.
Published: (2024)
by: Lu, Yiwei, et al.
Published: (2024)
Large Language Models Are Zero-Shot Time Series Forecasters
by: Gruver, Nate, et al.
Published: (2023)
by: Gruver, Nate, et al.
Published: (2023)
SeqFusion: Sequential Fusion of Pre-Trained Models for Zero-Shot Time-Series Forecasting
by: Huang, Ting-Ji, et al.
Published: (2025)
by: Huang, Ting-Ji, et al.
Published: (2025)
Pre-training Epidemic Time Series Forecasters with Compartmental Prototypes
by: Liu, Zewen, et al.
Published: (2025)
by: Liu, Zewen, et al.
Published: (2025)
TempoPFN: Synthetic Pre-training of Linear RNNs for Zero-shot Time Series Forecasting
by: Moroshan, Vladyslav, et al.
Published: (2025)
by: Moroshan, Vladyslav, et al.
Published: (2025)
Zero Shot Time Series Forecasting Using Kolmogorov Arnold Networks
by: Bhattacharya, Abhiroop, et al.
Published: (2024)
by: Bhattacharya, Abhiroop, et al.
Published: (2024)
Using Pre-trained LLMs for Multivariate Time Series Forecasting
by: Wolff, Malcolm L., et al.
Published: (2025)
by: Wolff, Malcolm L., et al.
Published: (2025)
Rethinking Uncertainty Estimation in LLMs: A Principled Single-Sequence Measure
by: Aichberger, Lukas, et al.
Published: (2024)
by: Aichberger, Lukas, et al.
Published: (2024)
A Diffusion Model Framework for Unsupervised Neural Combinatorial Optimization
by: Sanokowski, Sebastian, et al.
Published: (2024)
by: Sanokowski, Sebastian, et al.
Published: (2024)
Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting
by: Madarasingha, Chamara, et al.
Published: (2025)
by: Madarasingha, Chamara, et al.
Published: (2025)
MIM-Refiner: A Contrastive Learning Boost from Intermediate Pre-Trained Representations
by: Alkin, Benedikt, et al.
Published: (2024)
by: Alkin, Benedikt, et al.
Published: (2024)
Generalisation Bounds of Zero-Shot Economic Forecasting using Time Series Foundation Models
by: Jetwiriyanon, Jittarin, et al.
Published: (2025)
by: Jetwiriyanon, Jittarin, et al.
Published: (2025)
Feature to Dynamics: Feature-space to Autoregression strategy for Zero-shot Time Series Forecasting
by: Wu, Yifan, et al.
Published: (2026)
by: Wu, Yifan, et al.
Published: (2026)
FlashRNN: I/O-Aware Optimization of Traditional RNNs on modern hardware
by: Pöppel, Korbinian, et al.
Published: (2024)
by: Pöppel, Korbinian, et al.
Published: (2024)
Revisiting LLMs as Zero-Shot Time-Series Forecasters: Small Noise Can Break Large Models
by: Park, Junwoo, et al.
Published: (2025)
by: Park, Junwoo, et al.
Published: (2025)
One-Embedding-Fits-All: Efficient Zero-Shot Time Series Forecasting by a Model Zoo
by: Shi, Hao-Nan, et al.
Published: (2025)
by: Shi, Hao-Nan, et al.
Published: (2025)
QuiZSF: A Retrieval-Augmented Framework for Zero-Shot Time Series Forecasting
by: Ma, Shichao, et al.
Published: (2025)
by: Ma, Shichao, et al.
Published: (2025)
Adapting to the Unknown: Robust Meta-Learning for Zero-Shot Financial Time Series Forecasting
by: Liu, Anxian, et al.
Published: (2025)
by: Liu, Anxian, et al.
Published: (2025)
MultiCast: Zero-Shot Multivariate Time Series Forecasting Using LLMs
by: Chatzigeorgakidis, Georgios, et al.
Published: (2024)
by: Chatzigeorgakidis, Georgios, et al.
Published: (2024)
Mamba4Cast: Efficient Zero-Shot Time Series Forecasting with State Space Models
by: Bhethanabhotla, Sathya Kamesh, et al.
Published: (2024)
by: Bhethanabhotla, Sathya Kamesh, et al.
Published: (2024)
TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting
by: Cao, Defu, et al.
Published: (2023)
by: Cao, Defu, et al.
Published: (2023)
Cross-RAG: Zero-Shot Retrieval-Augmented Time Series Forecasting via Cross-Attention
by: Lee, Seunghan, et al.
Published: (2026)
by: Lee, Seunghan, et al.
Published: (2026)
TimelyGPT: Extrapolatable Transformer Pre-training for Long-term Time-Series Forecasting in Healthcare
by: Song, Ziyang, et al.
Published: (2023)
by: Song, Ziyang, et al.
Published: (2023)
FAF: A Feature-Adaptive Framework for Few-Shot Time Series Forecasting
by: Ouyang, Pengpeng, et al.
Published: (2025)
by: Ouyang, Pengpeng, et al.
Published: (2025)
Benchmarking Pathology Feature Extractors for Whole Slide Image Classification
by: Wölflein, Georg, et al.
Published: (2023)
by: Wölflein, Georg, et al.
Published: (2023)
One-for-All: A Lightweight Stabilized and Parameter-Efficient Pre-trained LLM for Time Series Forecasting
by: Dey, Prasanjit, et al.
Published: (2026)
by: Dey, Prasanjit, et al.
Published: (2026)
Performance of Zero-Shot Time Series Foundation Models on Cloud Data
by: Toner, William, et al.
Published: (2025)
by: Toner, William, et al.
Published: (2025)
Timer: Generative Pre-trained Transformers Are Large Time Series Models
by: Liu, Yong, et al.
Published: (2024)
by: Liu, Yong, et al.
Published: (2024)
xLSTM: Extended Long Short-Term Memory
by: Beck, Maximilian, et al.
Published: (2024)
by: Beck, Maximilian, et al.
Published: (2024)
TS-RAG: Retrieval-Augmented Generation based Time Series Foundation Models are Stronger Zero-Shot Forecaster
by: Ning, Kanghui, et al.
Published: (2025)
by: Ning, Kanghui, et al.
Published: (2025)
TripCast: Pre-training of Masked 2D Transformers for Trip Time Series Forecasting
by: Liao, Yuhua, et al.
Published: (2024)
by: Liao, Yuhua, et al.
Published: (2024)
Addressing Pitfalls in the Evaluation of Uncertainty Estimation Methods for Natural Language Generation
by: Ielanskyi, Mykyta, et al.
Published: (2025)
by: Ielanskyi, Mykyta, et al.
Published: (2025)
Tiled Flash Linear Attention: More Efficient Linear RNN and xLSTM Kernels
by: Beck, Maximilian, et al.
Published: (2025)
by: Beck, Maximilian, et al.
Published: (2025)
Similar Items
-
TiRex: Zero-Shot Forecasting Across Long and Short Horizons with Enhanced In-Context Learning
by: Auer, Andreas, et al.
Published: (2025) -
Simplified priors for Object-Centric Learning
by: Patil, Vihang, et al.
Published: (2024) -
Zero-Shot Time Series Forecasting with Covariates via In-Context Learning
by: Auer, Andreas, et al.
Published: (2025) -
xLSTM Scaling Laws: Competitive Performance with Linear Time-Complexity
by: Beck, Maximilian, et al.
Published: (2025) -
Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series
by: Ekambaram, Vijay, et al.
Published: (2024)