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arXiv Machine Learning By Morad Laglil, Bertrand Pracca, Emilie Devijver, Eric Gaussier

Foundation Models and Fine-Tuning: Toward a New Generation of Models for Time Series Forecasting

Read the original on arXiv Machine Learning →

arXiv:2607. 23146v1 Announce Type: new Abstract: Inspired by recent breakthroughs in large language models for natural language processing, foundation models have emerged as a promising paradigm for zero-shot time series forecasting, enabling accurate predictions on datasets never seen during pre-training.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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