Time-Series Foundation Models

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Overview

Time-series foundation models learn reusable patterns from large collections of sequences, aiming to support tasks such as forecasting, classification, imputation, and anomaly detection across domains. Common approaches include Transformer models with patch or value tokenization, masked and contrastive pretraining, next-token prediction, and newer recurrent or state-space architectures; training data may mix real series with synthetic ones. Models are used zero-shot or adapted through fine-tuning, in-context examples, covariates, retrieval, and lightweight adapters, with benchmarks such as GIFT-Eval and UCR/UEA testing different capabilities. Transfer can reduce the need for task-specific training, but results vary with data and operating conditions: specialists may still win, and robustness to distribution shifts, long contexts, uncertainty, and fair evaluation remain open challenges.

Latest papers

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304 papers69 papers in the last four weeks, up 86% on the four weeks before. 0.4% of all new papers.

  1. TEDDY: A Pediatric Foundation Model for Risk Forewarning from ICD-Coded Diagnostic Histories

    Jul 15, 2026Matthew Brady Neeley, Jorge Botas, Johnathan Jia +5EHR Foundation ModelsClinical Prediction

    Baylor College of Medicine

  2. The Spectrum Is Not Enough: When Context Helps Time-Series Forecasting

    Jul 14, 2026Mert Onur Cakiroglu, Mehmet Dalkilic, Hasan KurbanTime Series ForecastingRetrieval-Augmented Time Series Forecasting

    Luddy School of Informatics, Computing, and Engineering, Indiana University Bloomington, Bloomington, IN, USA · College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar

  3. Exploring Zero-Shot Foundation Models for Multivariate Time Series Anomaly Detection

    Jul 14, 2026Martin Uray, Saverio Messineo, Roland Kwitt +1Industrial Anomaly DetectionZero-Shot Anomaly Detection

    Josef Ressel Centre for Intelligent and Secure Industrial Automation, Salzburg University of Applied Sciences, Austria · Department of Artificial Intelligence and Human Interfaces, Paris Lodron University of Salzburg, Austria

  4. NeuroECG: ECGFounder-Based Deep ECG Representation for EEG-Free Neurological Prognostication After Cardiac Arrest

    Jul 13, 2026Jiajun Gao, Yi Zhao, Chenyang Xu +2Representation LearningHealthcare

    School of Economics and Management Xidian University Xi’an, China · School of Mechano-Electronic Engineering Xidian University Xi’an, China · School of Cyber Engineering Xidian University Xi’an, China +1

  5. Evaluating the Generalizability of Foundation Models for Extreme Environmental Events: Case Study of California Wildfire PM2.5

    Jul 8, 2026Yongcan Huang, Li Jiang, Ze Yu LiuWildfire ForecastingOOD Generalization

    College of Engineering, University of Georgia, Athens, Georgia, USA · Information System Department, UMBC, Baltimore, Maryland, USA · College of Graduate and Professional Studies, Trine University, Angola, Indiana, USA +1

  6. TimEE: End-to-end Time Series Classification via In-Context Learning

    Jul 8, 2026Jaris Küken, Shi Bin Hoo, Martin Mráz +2Synthetic Data PretrainingTime Series Classification

    University of Freiburg · Zuse School ELIZA Darmstadt · Prior Labs +1

  7. Physical activities enable scalable foundation modelling for broad-spectrum health prediction

    Jul 8, 2026Zhenghuang Wu, Yuyao Zhu, Songlin XuWearable Health MonitoringTime-Series Foundation Models

    Beihang University, Beijing, China · University of Science and Technology of China, Hefei, China · The Hong Kong Polytechnic University, Hong Kong SAR, China

  8. RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models

    Jul 7, 2026Qian Sun, Yong-Ming Tian, Jia-Wei Huang +2Synthetic Data PretrainingMultivariate Time Series Forecasting

    State Key Laboratory of Novel Software Technology, Nanjing University, Nanjing, China · School of Intelligent Science and Technology, Nanjing University, Suzhou, China · Nanjing University – Siemens Joint Research Center on Industrial AI, Suzhou, China +1

  9. Inertia-1: An Open Exploration of Wearable Motion Foundation Models

    Jul 7, 2026Zongzhe Xu, Aakarsh Anand, Sarah Jiang +4Human Activity RecognitionWearable Sensing

    University of California, Los Angeles · Duke University · John Hopkins University

  10. When Do Foundation Models Pay Off? A Break-Even Analysis of Pretrained Time Series Forecasters

    Jul 6, 2026Nicholas Tan Jerome, Frank SimonZero-Shot Time Series ForecastingTime Series Forecasting

    Karlsruhe Institute of Technology (KIT) Eggenstein-Leopoldshafen, Germany

  11. MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms

    Jul 3, 2026Saiyang Feng, Yuanyun Zhang, Shi LiSelf-Supervised Time Series Representation LearningCross-Modal Representation Learning

    University of the Chinese Academy of Sciences · Columbia University

  12. Modular Foundation Models for Time-Series Perception in Digital Twins

    Jul 3, 2026Quang Hung Pham, Ryad Zemouri, Martin Gagnon +1Self-Supervised Time Series Representation LearningTime Series Forecasting

    Hydro-Québec · 75, boulevard René-Lévesque Ouest · Montréal, Québec, Canada

  13. QuantFlow: A Federated Mamba-Based Post-Transformer Foundation Model for Time-Series Forecasting

    Jul 2, 2026Shah Nawaz Haider, Steve Austin, Arnab Barua +2Selective SSMsTime Series Forecasting

    Department of Computer Science and Engineering, University of Science and Technology Chittagong · Department of Electrical and Electronic Engineering, University of Science and Technology Chittagong · Faculty of Science, Engineering and Technology, University of Science and Technology Chittagong

  14. Evaluating Time Series Foundation Models for Electricity Price Forecasting: Contamination Risk, Distributional Shifts, and Covariate Dependence

    Jul 2, 2026Zhenghua Pan, Ahmed Aziz EzzatZero-Shot Time Series ForecastingElectricity Price Forecasting

    Department of Industrial & Systems Engineering, Rutgers, The State University of New Jersey, USA.

  15. Probabilistic Low-Voltage Peak Load Forecasting with Time Series Foundation Models Evaluated on Application-Oriented Metrics

    Jul 2, 2026Benedikt Kaas, Manuel Treutlein, Hannes Benedikt Gerber +5Time Series ForecastingElectricity Load Forecasting

    Karlsruhe Institute of Technology (KIT), Germany and Netze BW GmbH, Germany · Netze BW GmbH, Germany · Karlsruhe Institute of Technology (KIT), Germany

  16. Zeus: Towards Tuning-Free Foundation Model for Time Series Analysis

    Jul 2, 2026Yisong Fu, Zezhi Shao, Chengqing Yu +4Zero-Shot Time Series ForecastingMulti-Task Learning

    State Key Laboratory of AI Safety, Institute of Computing Technology, Chinese Academy of Sciences · University of Chinese Academy of Sciences · Xiamen Institute of Data Intelligence

  17. TiRex-2: Generalizing TiRex to Multivariate Data and Streaming

    Jul 1, 2026Patrick Podest, Marco Pichler, Elias Bürger +7Multivariate Time Series ForecastingZero-Shot Time Series Forecasting

    ELLIS Unit Linz, LIT AI Lab & Institute for Machine Learning, JKU Linz, Austria · NXAI Lab, Linz, Austria · NXAI GmbH, Linz, Austria +1

  18. CLOUDADV: Decision-Aligned Instance Sizing with Zero-Shot Foundation Models under Drift

    Jun 30, 2026Jack Bell, Giacomo Carfi, Gerlando Gramaglia +3AI-Assisted Decision MakingCloud Computing

    Department of Computer Science University of Pisa Pisa, Italy · Independent Researcher Sintra Consulting Limited Arezzo, Italy · Department of AI, Data and Decision Science Luiss University Rome, Italy

  19. Temporal Feature Extractors in EEG Foundation Models: A Controlled Comparison Including a Pretrained Time-Series Model

    Jun 29, 2026Ayşe Betül Yüce, Chris Joey Leffler, Sarun Varghese +2EEG DecodingTime-Series Foundation Models

    Otto von Guericke University Magdeburg, Artificial Intelligence Lab, Faculty of Computer Science, Magdeburg, Germany · Otto von Guericke University Magdeburg, Knowledge Management and Discovery Lab, Faculty of Computer Science, Magdeburg, Germany

  20. MACROCAST: A Vintage-Consistent Time Series Foundation Model for Real-Time Macroeconomic Forecasting

    Jun 27, 2026Andrea Carriero, Davide Pettenuzzo, Shubhranshu ShekharData LeakageTime Series Forecasting

    School of Economics and Finance, Queen Mary University of London. · School of Business and Economics, Brandeis University.

  21. NIVA: A Multimodal Foundation Model for Actionable Earth System Intelligence

    Jun 26, 2026Anisha Pal, Aodhan Sweeney, Kyle Heyblom +1Climate ScienceMultimodal Pretraining

    Independent Researcher · Work done while at Planette AI · Planette AI, USA.

  22. Are Time-Series Foundation Models Ready for E-Nose Data? An Empirical Assessment of Their Embeddings

    Jun 26, 2026Taeyeong Choi, Mohammed KamruzzamanTime Series ClassificationTime Series Representation Learning

    Department of Information Technology Kennesaw State University Marietta, GA 30060, USA · Department of Agricultural and Biological Engineering University of Illinois Urbana-Champaign Urbana, IL 61801, USA

  23. Unified Zero-Shot Time Series Forecasting: A Darts Foundation

    Jun 25, 2026Zhihao Dai, Dennis Bader, Alain GysiZero-Shot Time Series ForecastingTime-Series Foundation Models

    Energy and Power Group, Department of Engineering Science, University of Oxford, UK · Unit8 SA, Switzerland

  24. RocketPFN: Accurate Time Series Classification via In-Context Learning

    Jun 19, 2026Franco Martino O'Rourke, Ana Trisovic, Dimitris BertsimasTime Series ClassificationClassification

  25. Understanding Key Features of Time Series Foundation Models from Epidemic Forecasting

    Jun 17, 2026Alireza Jafari, Judy Fox, Geoffrey C. Fox +2Epidemic ForecastingLLM-Based Time Series Forecasting

    Department of Computer Science, School of Engineering and Applied Science, University of Virginia, Charlottesville, VA 22904 USA · School of Data Science, University of Virginia, Charlottesville, VA 22904 USA · Biocomplexity Institute and the Department of Computer Science, School of Engineering and Applied Science, University of Virginia, Charlottesville, VA 22904 USA +1

  26. Do Time Series Foundation Model Benchmarks Hide Regime-Dependent Failures? Evidence from Traffic Speed Forecasting

    Jun 16, 2026Yingshuo Wang, Xian Sun, Lingdong Kong +4Time Series ForecastingForecasting Benchmarks

    University of California, Berkeley, CA, USA · Duke University, Durham, NC, USA · National University of Singapore, Singapore +3

  27. TimeVista: Exploring and Exploiting Vision-Language Models as Judges for Time Series Forecasting

    Jun 15, 2026Zhi Chen, Yuxuan Wang, Jialong Wu +5VLM EvaluationForecasting Benchmarks

    School of Software, BNRist, Tsinghua University, Beijing 100084, China

  28. A Comparative Study of Deep Learning Architectures for Multi-Horizon Behavioural Forecasting for Mobile Health

    Jun 12, 2026Pavlos Nicolaou, Kleanthis Malialis, Artemis Kontou +1Zero-Shot Time Series ForecastingTime Series Forecasting

    KIOS Research and Innovation Center of Excellence · Department of Computer Science University of Cyprus, Nicosia, Cyprus

  29. Learning the Context of Errors: Black-Box Online Adaptation of Time Series Foundation Models

    Jun 12, 2026Xilin Dai, Yiding Liu, Hongjie Xia +4Test-Time AdaptationResidual Learning

    Ant International · The Chinese University of Hong Kong

  30. Beyond Uniform Tokens: Adaptive Compression for Time Series Language Models

    Jun 11, 2026Jialin Gan, Xin Qiu, Guangzhe Chen +1LLM Inference AccelerationMultimodal Token Compression

    Zhejiang University · Harbin Institute of Technology · Shandong University