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AutoPrune enables LLMs to autonomously design visual-token pruning strategies, achieving a remarkable 9.9x reduction in FLOPs without sacrificing performance.
Action-conditioned world models can be misled by statistical biases, but a new framework shows how to enforce true action dynamics for superior performance.
