SOURCE-LINKED INTELLIGENCE
SMart: A Multi-source Multi-phase Time Series Representation Transfer Framework
Time series representation learning (TSRL) has attracted growing research interests in recent years. Two recent explorations in TSRL are: i) exploiting a transformer-based framework to learn time series; ii) instead of using only the targeted dataset, borrowing time series from other datasets to to facilitate representation transfer. While these two explorations are shown effective, the self-supervised time series recovery task in (i) and the single-source dataset used in (ii) are technically simple and thus can be enhanced with new ideas. In this work, we propose a new TSRL framework, namely
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-02T07:12:39.000Z
First collected: 2026-09-21T05:51:54.566Z. This is not the publication date.