Self-Supervised Latent Action-Conditioned World Modeling for Time Series
arXiv:2610.37963v1 Announce Type: new 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 t…
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- 2026-10-30 04:00 · arXiv cs.LG
Self-Supervised Latent Action-Conditioned World Modeling for Time Series