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Batch normalization's power comes from reshaping the geometry of neural network decision boundaries on a per-batch basis, not just from optimization benefits.
Predefined interaction vocabularies are holding back HOI detection, but MLLMs can unlock truly unconstrained understanding of how humans and objects interact.
