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News/Self-Supervised Latent Action-Conditioned World Modeling for Time Series
arxiv
PublishedOctober 31, 2026 at 4:00 AM

Self-Supervised Latent Action-Conditioned World Modeling for Time Series

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arXiv:2610.37963v1 Announce Type: cross Abstract: Time-series data play an important role in various tasks, such as weather forecasting, web traffic analysis, and speech recognition. Recently, pioneering studies have increasingly adopted Joint-Embedding Predictive Architecture (JEPA) based encoders

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