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Fudan University
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DeepRubric achieves comparable performance to state-of-the-art models while slashing reinforcement learning resource consumption by 13 times.
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.
