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Light-WAM Code in Practice: Directly Decoding Robot Actions with a Frozen Video World Model

This practical project centers on the core Light-WAM code, analyzing how it uses a frozen video world model, an Adapter, and a State Fusion mechanism to directly decode robot actions in a more lightweight way while retaining future-prediction capability.

Part of the event: Light-WAM Code in Practice: Directly Decoding Robot Actions with a Frozen Video World Model

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