Zero-Shot Forecasting

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4 papers in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

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Foundations without Fundamentals: Zero-Shot Blind Spots in Time Series FMs
Oct 1, 2026Nafiseh Ghoroghchian, Haipeng Zhang, Shuyi Han +2Time Series Foundation Models Zero-Shot Forecasting
Layer6 AI
Evaluating Accuracy and Probabilistic Reliability of Zero-Shot Time Series Foundation Models
Sep 22, 2026Panagiotis Michael, Moysis Symeonides, Demetris TrihinasZero-Shot Forecasting Cnn-Lstm
Department of Computer Science, University of Nicosia, Cyprus · Department of Computer Science, University of Cyprus, Cyprus
QUALS: Corpus Equilibrium for Universal Forecasting via Pattern Quantization and Learnability Synchronization
Sep 17, 2026Yujie Li, Zezhi Shao, Chengqing Yu +7Zero-Shot Forecasting Pretraining
State Key Laboratory of AI Safety, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China · University of Chinese Academy of Sciences, Beijing, China · School of Data Science and Engineering, East China Normal University, Shanghai, China
Distilling Foundation Models for Agentic What-If Reasoning:Cost, Latency, and Governance in a Hybrid LLM+SLM Architecture
Sep 14, 2026Sourish Dey, Aditya KumarTabular Foundation Models Agentic Reasoning
Machine Learning SumUp, Berlin
Systematic Evaluation of TabPFN-TS and Chronos-2 for Zero-Shot Heat Load Forecasting in District Heating Networks
Aug 20, 2026Ben Spoek, Karim K. Ben Hicham, Kai Derzsi +3Accurate Short-Term Electricity Load Forecasting Zero-Shot Forecasting
Chair of Energy Efficient Buildings and Indoor Climate, RWTH Aachen University, Mathieustr. 10, 52074 Aachen, Germany · Process Systems Engineering, RWTH Aachen University, Forckenbeckstr. 51, 52074 Aachen, Germany
Into the ORBIT for Time Series: Training Regimes for Foundation Models
Aug 13, 2026Hongjie Xia, Yiding Liu, Yifan Hu +2Time Series Foundation Models Zero-Shot Forecasting
Foundation Models and Fine-Tuning: Toward a New Generation of Models for Time Series Forecasting
Jul 25, 2026Morad Laglil, Bertrand Pracca, Emilie Devijver +1Zero-Shot Forecasting Time Series Forecasting
Savoye, 18 bd des Gorgets, 21000, Dijon, France · Univ. Grenoble Alpes, CNRS, Grenoble INP, LIG, Grenoble, 38000, France
Zero-Shot Heart Rate Variability Forecasting from Consumer Wearables Using Time Series Foundation Models
Jul 22, 2026Luukas Peräkylä, Fahad Sohrab, Ville Hautamäki +3Time Series Foundation Models Heart Rate
Tampere University, Tampere, Finland · University of Eastern Finland, Finland
Towards Reliable Zero-Shot Crowd Forecasting: Evaluating Time Series Foundation Models for Special Event Pedestrian Forecasting
Jul 20, 2026Ziteng Li, Yanan Xin, Tina Comes +1Zero-Shot Forecasting Pedestrian Trajectory Prediction
Delft University of Technology (TU Delft), Department of Transport & Planning, Delft, The Netherlands. · Delft University of Technology (TU Delft), Technology, Policy and Management, Delft, The Netherlands. · German Aerospace Center (DLR), Institute for the Protection of Terrestrial Infrastructures, Sankt Augustin, Germany.
Lightweight Wrappers for Adapting Time Series Foundation Models to Regional Drought Forecasting
Jul 20, 2026Wentao Gao, Jiuyong Li, Lin Liu +4Time Series Foundation Models Zero-Shot Forecasting
Adelaide University · Adelaide, Australia · CSIRO Technology +1
A Minimal Interpretable Architecture for Zero-Shot Reconstruction of Dynamical Systems
Jul 16, 2026Christoph Jürgen Hemmer, Florian Plaswig, Daniel DurstewitzZero-Shot Forecasting Dynamical Systems
Dept. of Theoretical Neuroscience, Central Institute of Mental Health, Mannheim, Germany · Interdisciplinary Center for Scientific Computing (IWR), Heidelberg, Germany · Faculty of Physics and Astronomy, Heidelberg University, Heidelberg, Germany
Rethinking Multimodal Time-Series Forecasting Evaluation
Jul 8, 2026Haoxin Liu, Yichen Zhou, Rajat Sen +2Zero-Shot Forecasting Time Series
Georgia Institute of Technology · Google Research
TopoBrick: Agentic Topology Sampling of Exogenous Variables for Zero-Shot Building IoT Forecasting
Jul 7, 2026Xiachong Lin, Du Yin, Arian Prabowo +6Zero-Shot Forecasting Internet Of Thing
University of New South Wales Sydney, NSW, Australia · Hong Kong University of Science and Technology (Guangzhou) Guangzhou, China · Mohamed bin Zayed University of Artificial Intelligence Abu Dhabi, United Arab Emirates +1
Evaluating Time Series Foundation Models for Electricity Price Forecasting: Contamination Risk, Distributional Shifts, and Covariate Dependence
Jul 2, 2026Zhenghua Pan, Ahmed Aziz EzzatElectricity Price Forecasting Time Series Foundation Models
Department of Industrial & Systems Engineering, Rutgers, The State University of New Jersey, USA.
Zeus: Towards Tuning-Free Foundation Model for Time Series Analysis
Jul 2, 2026Yisong Fu, Zezhi Shao, Chengqing Yu +4Time Series Foundation Models Zero-Shot Forecasting
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
CLOUDADV: Decision-Aligned Instance Sizing with Zero-Shot Foundation Models under Drift
Jun 30, 2026Jack Bell, Giacomo Carfi, Gerlando Gramaglia +3Cloud Zero-Shot Forecasting
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
Unified Zero-Shot Time Series Forecasting: A Darts Foundation
Jun 25, 2026Zhihao Dai, Dennis Bader, Alain GysiZero-Shot Forecasting Data-Driven Forecasting
Energy and Power Group, Department of Engineering Science, University of Oxford, UK · Unit8 SA, Switzerland
Learning the Context of Errors: Black-Box Online Adaptation of Time Series Foundation Models
Jun 12, 2026Xilin Dai, Yiding Liu, Hongjie Xia +4Time Series Foundation Models Zero-Shot Forecasting
Ant International · The Chinese University of Hong Kong
CloudCons: A Comprehensive End-to-End Benchmark for Cloud Resource Consolidation
Jun 11, 2026Xiaobin Zhang, Lefei Shen, Mouxiang Chen +6Zero-Shot Forecasting Time Series Foundation Models
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 +1Zero-Shot Forecasting Time Series Foundation Models
Research & Development Group, Hitachi Ltd., Tokyo, Japan
Causal Semantic Alignment for LLM-based Time Series Forecasting
Jun 6, 2026Kexuan Zhang, Xiaobei Zou, Cesare Alippi +2Zero-Shot Forecasting Time Series
GITCO: Gated Inference-Time Context Optimization in TSFMs
Jun 3, 2026Manya Pandey, Dhruv Kumar, Murari Mandal +1Time Series Foundation Models Zero-Shot Forecasting
Birla AI Labs, Mumbai, India · KIIT, Bhubaneswar, India · BITS Pilani, Pilani, India
Feature to Dynamics: Feature-space to Autoregression strategy for Zero-shot Time Series Forecasting
May 31, 2026Yifan Wu, Junjie Wu, Kai Wu +2Zero-Shot Forecasting Time Series
School of Artificial Intelligence, Xidian University, Xi’an, China · School of Cyber Engineering, Xidian University, Xi’an, China · Sun Yat-Sen University, Guangzhou, China
Rethinking Post-Training Recipes for Multimodal Time-Series Forecasting
May 28, 2026Haoxin Liu, Yichen Zhou, Rajat Sen +2Zero-Shot Forecasting Time Series Foundation Models
Georgia Institute of Technology · Google Research
Factorize to Generalize: Retrieval-Guided Invariant-Dynamic Decomposition for Time Series Forecasting
May 24, 2026Jinjin Chi, Lei Feng, Lulu Zhang +6Zero-Shot Forecasting Time Series Forecasting
College of Computer Science and Technology, Jilin University, Changchun, China · College of Computing and Data Science, Nanyang Technological University, Singapore · City St George’s, University of London, London, United Kingdom +1
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 +1Electricity Price Forecasting Time Series Foundation Models
ELECTA-ESAT (KU Leuven) Leuven, Belgium · ELECTA-ESAT(KU Leuven) and Gridual Leuven, Belgium
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 Forecasting Time Series Forecasting
LG AI Research Seoul, South Korea
ChronoSteer: Bridging Large Language Model and Time Series Foundation Model via Synthetic Cross-Modal Alignment Dataset
May 15, 2025Chengsen Wang, Qi Qi, Zhongwen Rao +2Zero-Shot Forecasting Time Series Foundation Models
Beijing University of Posts and Telecommunications · Huawei Noah’s Ark Lab

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Foundations without Fundamentals: Zero-Shot Blind Spots in Time Series FMs

Nafiseh Ghoroghchian, Haipeng Zhang, Shuyi Han, Alex Labach+1

Layer6 AI

Time Series Foundation Models Zero-Shot Forecasting Zero-Shot Robustness Inductive Bias

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Despite the success of Time Series Foundation Models (TSFMs) on broad benchmarks, their ability to internalize basic temporal logic, especially in settings supported by exogenous covariates, remains under-examined. We introduce SimpleTimeBench, a diagnostic univariate and multivariate "unit test" suite for primitives such as monotonic trends, periodic signals and leading indicator covariates, scenarios where near-perfect forecasts should be trivial. Surprisingly, prominent multivariate TSFMs (Chronos-2, Moirai and Toto) frequently produce suboptimal zero-shot forecasts for these inputs. While fine-tuning Chronos-2 improves its behaviour on specific tasks, we show that this adaptation degrades performance on other fundamental patterns rather than enhancing its generalizable foundational capabilities. This reveals a gap between pre-training scale and basic temporal reasoning, suggesting that current TSFMs could potentially lack the inductive biases needed to capture simple predictable functions. We further demonstrate that these failures are not merely synthetic curiosities: they persist in real-world sensor forecasting, where TSFMs consistently underutilize leading indicators available in observed covariates. This inability to capture simple relationships limits the practical utility and reliability of current multivariate models.

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