Are Time-Indexed Foundation Models the Future of Time Series Imputation?

• URL: http://arxiv.org/abs/2511.05980v1
• Date: Sat, 08 Nov 2025 11:57:33 GMT
• Title: Are Time-Indexed Foundation Models the Future of Time Series Imputation?
• Authors: Etienne Le Naour, Tahar Nabil, Adrien Petralia, Ghislain Agoua,
• Abstract summary: Two models, TabPFN-TS and MoTM, share a common philosophy that places them within the family of time-indexed foundation models.<n>This paper presents the first large-scale empirical study of these models for zero-shot imputation.
• Score: 0.6999740786886536
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Foundation models for time series imputation remain largely unexplored. Recently, two such models, TabPFN-TS and MoTM, have emerged. These models share a common philosophy that places them within the family of time-indexed foundation models. This paper presents the first large-scale empirical study of these models for zero-shot imputation, which enables missing value recovery without retraining across a wide range of scenarios. We conduct extensive univariate experiments across 33 out-of-domain datasets (approximately 1.3M imputation windows) and evaluate their ability to integrate covariates at inference time to improve accuracy without fine-tuning. Our results demonstrate that time-indexed foundation models are a powerful and practical step toward achieving general-purpose, zero-shot imputation for real-world time series.

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