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Achieving 74.419% accuracy, this ensemble approach shows that self-supervised learning can dramatically enhance micro-gesture recognition performance.
MiniMax-M2 proves that massive parameter counts don't always translate to better agentic performance; strategic activation of a smaller subset can unlock frontier-level intelligence.
