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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.
Stop training your captioning models with blunt instruments: ClaimDiff-RL uses verifiable, typed claim differences to expose the faithfulness/coverage tradeoff and enable more balanced, controllable caption generation.
