Enhancing Latent World Models with Associative Memory
A memory-enhanced latent world model that augments JEPA-style prediction with a content-addressable memory bank is introduced that achieves state-of-the-art performance with a lightweight architecture, outperforming conventional latent world models on long-horizon planning tasks.
Yu-Wei Sun, Si-Yu Zhu
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