Zero-Shot Time Series Forecasting

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7 papers in the last four weeks, up 75% on the four weeks before. 0.1% of all new papers.

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CloudCons: A Comprehensive End-to-End Benchmark for Cloud Resource Consolidation
Jun 11, 2026Xiaobin Zhang, Lefei Shen, Mouxiang Chen +6Zero-Shot Time Series Forecasting Forecasting Benchmarks
Zhejiang University Hangzhou, China · State Street Technology (Zhejiang) Ltd. Hangzhou, China · Richoo AI Hangzhou, China +2
CITRAS-FM: Tiny Time Series Foundation Model for Covariate-Informed Zero-Shot Forecasting
Jun 9, 2026Yosuke Yamaguchi, Issei Suemitsu, Yuki Kajihara +1Synthetic Data Pretraining Zero-Shot Time Series Forecasting
Research & Development Group, Hitachi Ltd., Tokyo, Japan
Tyan-WP: A Wind Power Foundation Model for Ultra-Short-Term Probabilistic Forecasting
Jun 7, 2026Jiahui Huang, Ao Luo, Lei Liu +6Zero-Shot Time Series Forecasting Time Series Forecasting
School of Information Science and Technology, University of Science and Technology of China, Hefei, 230022, China · China Electric Power Research Institute, Beijing, 100192, China
InA-Probe: Instruction-Aware Active Probing for Time Series Forecasting with LLMs
Jun 7, 2026Peiliang Gong, Emadeldeen Eldele, Chenyu Liu +8Zero-Shot Time Series Forecasting Time Series Forecasting
College of Computing and Data Science, Nanyang Technological University, Singapore · Department of Computer Science, Khalifa University, UAE · Key Laboratory of Brain-Machine Intelligence Technology, Ministry of Education, College of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China +1
Time series Foundation Models based on Physics-Informed Synthetic Histories for Cold-Start Photovoltaic Forecasting
Jun 5, 2026Lorenzo Longarini, Alessandro Rongoni, Simone Silenzi +2Zero-Shot Time Series Forecasting Time Series Forecasting
Sistemi 2000 srl, Civitanova Marche, Italy · Department of Engineering ”Enzo Ferrari”, University of Modena and Reggio Emilia, Modena, Italy · Department of Political Sciences, Communication and International Relations, University of Macerata, Macerata, Italy
GlucoFM-Bench: Benchmarking Time-Series Foundation Models for Blood Glucose Forecasting
Jun 5, 2026Baiying Lu, Zhaohui Liang, Ryan Pontius +2Zero-Shot Time Series Forecasting Time Series Forecasting
Department of Computer Science Dartmouth College Hanover, NH 03784 · Department of Computer Science Emory University Atlanta, GA 30322 · Quantitative Biomedical Sciences Dartmouth College Hanover, NH 03784
GITCO: Gated Inference-Time Context Optimization in TSFMs
Jun 3, 2026Manya Pandey, Dhruv Kumar, Murari Mandal +1Zero-Shot Time Series Forecasting Inference-Time Optimization
Birla AI Labs, Mumbai, India · KIIT, Bhubaneswar, India · BITS Pilani, Pilani, India
Time Series as Language: A Universal Tokenizer for General-Purpose Time Series Foundation Models
May 31, 2026Yunhao Zhang, Ruiying Qi, Jiale Zheng +3Zero-Shot Time Series Forecasting Time Series Generation
Shanghai Jiao Tong University · Huawei Noah’s Ark Lab
Feature to Dynamics: Feature-space to Autoregression strategy for Zero-shot Time Series Forecasting
May 31, 2026Yifan Wu, Junjie Wu, Kai Wu +2Zero-Shot Time Series Forecasting Time Series Forecasting
School of Artificial Intelligence, Xidian University, Xi’an, China · School of Cyber Engineering, Xidian University, Xi’an, China · Sun Yat-Sen University, Guangzhou, China
KairosAgent: Agentic Time Series Forecasting with Fused Semantic Reasoning
May 28, 2026Kun Feng, Ziwei Shan, Yuchen Fang +6Multivariate Time Series Forecasting Zero-Shot Time Series Forecasting
ShanghaiTech University · Ant Group
Falcon-X: A Time Series Foundation Model for Heterogeneous Multivariate Modeling
May 26, 2026Yiding Liu, Yifan Hu, Hongjie Xia +5Multivariate Time Series Forecasting Zero-Shot Time Series Forecasting
ROAR: Retrieval Opportunity-Aware Refinement for Zero-Shot Time Series Forecasting
May 24, 2026Jinjin Chi, Lei Feng, Yiming Wang +4Zero-Shot Time Series Forecasting Time Series Forecasting
College of Computer Science and Technology, Jilin University, Changchun, China · College of Computing and Data Science, Nanyang Technological University, Singapore
Assessing the Operational Viability of Foundation Models for Time Series Forecasting
May 23, 2026Kavin Soni, Debanshu Das, Vamshi GuduguntlaZero-Shot Time Series Forecasting Time Series Forecasting
Google, USA
Olivia: Harmonizing Time Series Foundation Models with Power Spectral Density
May 17, 2026Jingru Fei, Kun Yi, Alex Xing Wang +3Zero-Shot Time Series Forecasting Frequency-Domain Feature Learning
Beijing Institute of Technology · North China Institute of Computing Technology · State Information Center +4
Empirical evaluation of Time Series Foundation Models for Day-ahead and Imbalance Electricity Price Forecasting in Belgium
May 16, 2026Chi Bui, Maria Margarida Mascarenhas, Arnaud Verstraeten +1Zero-Shot Time Series Forecasting Electricity Price Forecasting
ELECTA-ESAT (KU Leuven) Leuven, Belgium · ELECTA-ESAT(KU Leuven) and Gridual Leuven, Belgium
ISOMORPH: A Supply Chain Digital Twin for Simulation, Dataset Generation, and Forecasting Benchmarks
May 12, 2026Zhizhen Zhang, Hyemin Gu, Benjamin J. Zhang +6Zero-Shot Time Series Forecasting Forecasting Benchmarks
University of Massachusetts Amherst · University of North Carolina · SRI International +1
Prior-Fitted Functional Flow: In-Context Generative Models for Pharmacokinetics
Apr 19, 2026César Ojeda, Niklas Hartung, Wilhelm Huisinga +6Zero-Shot Time Series Forecasting Healthcare
University of Potsdam, Germany · Technical University Berlin, Germany · Freie Universität Berlin, Germany +2
Predicting Power-System Dynamic Trajectories with Foundation Models
Apr 16, 2026Haoran Li, Lihao Mai, Chenhan Xiao +2Neural Surrogate Modeling Zero-Shot Time Series Forecasting
School of Electrical, Computer and Energy Engineering at Arizona State University, Tempe, AZ 85281 USA · MOVEJ Analytics, Dayton, OH 45324 USA
A Foundation Model for Instruction-Conditioned In-Context Time Series Tasks
Mar 23, 2026Anish Saha, Konstantin ShmakovZero-Shot Time Series Forecasting Meta-Learning
Walmart Sunnyvale, USA
Not All Retrievals are Useful: Cross-Attention for Input-Aware RAG in Time Series Forecasting
Mar 16, 2026Seunghan Lee, Jaehoon Lee, Jun Seo +7Zero-Shot Time Series Forecasting Cross-Attention
LG AI Research Seoul, South Korea
Time Series Foundation Models for Process Model Forecasting
Dec 8, 2025Yongbo Yu, Jari Peeperkorn, Johannes De Smedt +1Zero-Shot Time Series Forecasting Process Mining
Research Center for Information Systems Engineering (LIRIS), KU Leuven, Belgium
Kairos: Toward Adaptive and Parameter-Efficient Time Series Foundation Models
Sep 30, 2025Kun Feng, Shaocheng Lan, Yuchen Fang +6Rotary Positional Embeddings Zero-Shot Time Series Forecasting
School of Information Science and Technology, ShanghaiTech University, Shanghai, China · Ant Group, Shanghai, China
ChronoSteer: Bridging Large Language Model and Time Series Foundation Model via Synthetic Cross-Modal Alignment Dataset
May 15, 2025Chengsen Wang, Qi Qi, Zhongwen Rao +2Cross-Modal Learning Multivariate Time Series Forecasting
Beijing University of Posts and Telecommunications · Huawei Noah’s Ark Lab

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CloudCons: A Comprehensive End-to-End Benchmark for Cloud Resource Consolidation

Xiaobin Zhang, Lefei Shen, Mouxiang Chen, Zhuo Li+5

Zhejiang University Hangzhou, China · State Street Technology (Zhejiang) Ltd. Hangzhou, China · Richoo AI Hangzhou, China+2

Zero-Shot Time Series Forecasting Forecasting Benchmarks Time-Series Foundation Models Probabilistic Time Series Forecasting

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Driven by conservative over-provisioning to guarantee service reliability, resource utilization in cloud data centers remains at low levels. To mitigate this, the forecast-then-optimize paradigm has emerged to optimize consolidation by anticipating future demands. While emerging time series foundation models promise to enhance this paradigm through zero-shot generalization, existing benchmarks focus solely on prediction error metrics. The actual decision utility of these advanced models remains unverified, rendering their practical value for downstream tasks uncertain. To bridge this gap, we propose CloudCons, a comprehensive end-to-end benchmark designed to evaluate forecasting models within the specific context of cloud resource consolidation. We build high-quality datasets that cover diverse workloads from Huawei Cloud, Microsoft Azure, and Google Borg, capturing distinct service characteristics ranging from synchronized diurnal rhythms to stochastic, pulse-like bursts and high-frequency noise. We conduct an extensive evaluation of statistical, deep learning, and foundation models. Our experiments reveal a pivotal finding: while foundation models demonstrate superior zero-shot forecasting accuracy, this advantage does not inherently translate into better decision utility. Of practical significance, we systematically analyze how the selection of predictive quantiles acts as a critical lever. We provide actionable guidelines for calibrating these selections to balance the trade-off between resource efficiency and service reliability, offering vital insights for real-world deployment decisions.

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