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Mixture of Memory Embeddings (MoME), a context-aware memory mechanism that replaces each token's single memory row with a mixture of M slots and uses a learned gate over the hidden state to choose which slots to read at each position, shows more promising memory-size scaling trend at sub-billion scale and remains effic...
This work introduces ZimaBlue, a scalable framework for learning generalizable World Action Models (WAMs) from large-scale video, and adopts an asynchronous Slow-Fast dual-system architecture to make generative WAMs practical for real-time control.
IDEEA (Input-Dependent stEEring via Activation cluster matching via Activation cluster matching), a training-free framework for input-dependent steering that aligns the model toward the target concept while preserving the input's original representation.
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