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Texas A&M University
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Latent world models often fail at planning not because their dynamics predictions are inaccurate, but because distorted control geometry makes the latent optimization landscape hostile to sampling-based search.
IS-SNN achieves state-of-the-art accuracy on ImageNet without the computational overhead of batch normalization, revolutionizing the efficiency of spiking neural networks.