Evaluating System 1 vs. 2 Reasoning Approaches for Zero-Shot Time Series Forecasting: A Benchmark and Insights
Fuente:
arXiv
Saved in:
| Main Authors: | Liu, Haoxin, Zhao, Zhiyuan, Li, Shiduo, Prakash, B. Aditya |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Performative Time-Series Forecasting
by: Zhao, Zhiyuan, et al.
Published: (2023)
by: Zhao, Zhiyuan, et al.
Published: (2023)
LSTPrompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term Prompting
by: Liu, Haoxin, et al.
Published: (2024)
by: Liu, Haoxin, et al.
Published: (2024)
Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant Learning
by: Liu, Haoxin, et al.
Published: (2024)
by: Liu, Haoxin, et al.
Published: (2024)
A Picture is Worth A Thousand Numbers: Enabling LLMs Reason about Time Series via Visualization
by: Liu, Haoxin, et al.
Published: (2024)
by: Liu, Haoxin, et al.
Published: (2024)
Tackling Time-Series Forecasting Generalization via Mitigating Concept Drift
by: Zhao, Zhiyuan, et al.
Published: (2025)
by: Zhao, Zhiyuan, et al.
Published: (2025)
TSI-Bench: Benchmarking Time Series Imputation
by: Du, Wenjie, et al.
Published: (2024)
by: Du, Wenjie, et al.
Published: (2024)
TimeRecipe: A Time-Series Forecasting Recipe via Benchmarking Module Level Effectiveness
by: Zhao, Zhiyuan, et al.
Published: (2025)
by: Zhao, Zhiyuan, et al.
Published: (2025)
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)
MultiCast: Zero-Shot Multivariate Time Series Forecasting Using LLMs
by: Chatzigeorgakidis, Georgios, et al.
Published: (2024)
by: Chatzigeorgakidis, Georgios, et al.
Published: (2024)
Time Series Foundation Models for Energy Load Forecasting on Consumer Hardware: A Multi-Dimensional Zero-Shot Benchmark
by: Simeone, Luigi
Published: (2026)
by: Simeone, Luigi
Published: (2026)
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)
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)
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)
Time Series Forecasting as Reasoning: A Slow-Thinking Approach with Reinforced LLMs
by: Zhou, Yitong, et al.
Published: (2025)
by: Zhou, Yitong, et al.
Published: (2025)
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)
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)
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)
Learning Graph Structures and Uncertainty for Accurate and Calibrated Time-series Forecasting
by: Kamarthi, Harshavardhan, et al.
Published: (2024)
by: Kamarthi, Harshavardhan, et al.
Published: (2024)
CSformer: Combining Channel Independence and Mixing for Robust Multivariate Time Series Forecasting
by: Wang, Haoxin, et al.
Published: (2023)
by: Wang, Haoxin, et al.
Published: (2023)
Reasoning-Aware Training for Time Series Forecasting
by: Ahamed, Md Atik, et al.
Published: (2026)
by: Ahamed, Md Atik, et al.
Published: (2026)
Let Experts Feel Uncertainty: A Multi-Expert Label Distribution Approach to Probabilistic Time Series Forecasting
by: Zhou, Zhen, et al.
Published: (2026)
by: Zhou, Zhen, et al.
Published: (2026)
VisionTS: Visual Masked Autoencoders Are Free-Lunch Zero-Shot Time Series Forecasters
by: Chen, Mouxiang, et al.
Published: (2024)
by: Chen, Mouxiang, et al.
Published: (2024)
AltTS: A Dual-Path Framework with Alternating Optimization for Multivariate Time Series Forecasting
by: Yuan, Zhihang, et al.
Published: (2026)
by: Yuan, Zhihang, et al.
Published: (2026)
HADL Framework for Noise Resilient Long-Term Time Series Forecasting
by: Dey, Aditya, et al.
Published: (2025)
by: Dey, Aditya, et al.
Published: (2025)
Rethinking Post-Training Recipes for Multimodal Time-Series Forecasting
by: Liu, Haoxin, et al.
Published: (2026)
by: Liu, Haoxin, et al.
Published: (2026)
TSI: A Multi-View Representation Learning Approach for Time Series Forecasting
by: Gao, Wentao, et al.
Published: (2024)
by: Gao, Wentao, et al.
Published: (2024)
Reverso: Efficient Time Series Foundation Models for Zero-shot Forecasting
by: Fu, Xinghong, et al.
Published: (2026)
by: Fu, Xinghong, et al.
Published: (2026)
MemCast: Memory-Driven Time Series Forecasting with Experience-Conditioned Reasoning
by: Tao, Xiaoyu, et al.
Published: (2026)
by: Tao, Xiaoyu, et al.
Published: (2026)
Seeking Universal Shot Language Understanding Solutions
by: Liu, Haoxin, et al.
Published: (2026)
by: Liu, Haoxin, et al.
Published: (2026)
An Adversarial Learning Approach to Irregular Time-Series Forecasting
by: Nam, Heejeong, et al.
Published: (2024)
by: Nam, Heejeong, et al.
Published: (2024)
TAT: Temporal-Aligned Transformer for Multi-Horizon Peak Demand Forecasting
by: Zhao, Zhiyuan, et al.
Published: (2025)
by: Zhao, Zhiyuan, et al.
Published: (2025)
Deep Frequency Derivative Learning for Non-stationary Time Series Forecasting
by: Fan, Wei, et al.
Published: (2024)
by: Fan, Wei, et al.
Published: (2024)
Exploring Progress in Multivariate Time Series Forecasting: Comprehensive Benchmarking and Heterogeneity Analysis
by: Shao, Zezhi, et al.
Published: (2023)
by: Shao, Zezhi, et al.
Published: (2023)
Can Slow-thinking LLMs Reason Over Time? Empirical Studies in Time Series Forecasting
by: Cheng, Mingyue, et al.
Published: (2025)
by: Cheng, Mingyue, et al.
Published: (2025)
Only the Curve Shape Matters: Training Foundation Models for Zero-Shot Multivariate Time Series Forecasting through Next Curve Shape Prediction
by: Feng, Cheng, et al.
Published: (2024)
by: Feng, Cheng, et al.
Published: (2024)
HEARTS: Benchmarking LLM Reasoning on Health Time Series
by: Li, Sirui, et al.
Published: (2026)
by: Li, Sirui, et al.
Published: (2026)
Rethinking Zero-Shot Time Series Classification: From Task-specific Classifiers to In-Context Inference
by: Fang, Juntao, et al.
Published: (2026)
by: Fang, Juntao, et al.
Published: (2026)
Training and Evaluating Causal Forecasting Models for Time-Series
by: Crasson, Thomas, et al.
Published: (2024)
by: Crasson, Thomas, et al.
Published: (2024)
Explainable and Interpretable Forecasts on Non-Smooth Multivariate Time Series for Responsible Gameplay
by: Jagirdar, Hussain, et al.
Published: (2025)
by: Jagirdar, Hussain, et al.
Published: (2025)
HDT: Hierarchical Discrete Transformer for Multivariate Time Series Forecasting
by: Feng, Shibo, et al.
Published: (2025)
by: Feng, Shibo, et al.
Published: (2025)
Similar Items
-
Performative Time-Series Forecasting
by: Zhao, Zhiyuan, et al.
Published: (2023) -
LSTPrompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term Prompting
by: Liu, Haoxin, et al.
Published: (2024) -
Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant Learning
by: Liu, Haoxin, et al.
Published: (2024) -
A Picture is Worth A Thousand Numbers: Enabling LLMs Reason about Time Series via Visualization
by: Liu, Haoxin, et al.
Published: (2024) -
Tackling Time-Series Forecasting Generalization via Mitigating Concept Drift
by: Zhao, Zhiyuan, et al.
Published: (2025)