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Author

Yongchao Huang

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Preprint Aug 2026

SJEPA: Learning Elegant Latent Dynamics with Hybrid Symbolic-Neural Predictors

Joint-embedding predictive architectures learn abstract states by predicting target embeddings from context embeddings, but their transition models are typically opaque neural maps. We introduce SJEPA, a reconstruction-free JEPA framework that learns predictive representations whose induced dynamics admit compact symbo...

Yong-Chao Huang · 0 citations
Preprint Aug 2026

Your Probabilistic JEPA Is Secretly a Hidden Markov Model: A State-Space Interpretation of Joint-Embedding Predictive Learning

A hidden Markov model (HMM) combines three roles: inference of a hidden-state belief from observations, propagation through a Markov transition, and emission back to observation space. We show that full, time-indexed Predictive Information Bottleneck VJEPA (PIB-VJEPA) exposes the same computational structure: a stochas...

Yongchao Huang · 0 citations

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