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Verified reliability outperforms domain expertise in teacher selection, leading to substantial performance gains in multi-domain LLMs.
MLLMs often start with the right visual predictions but override them for text, and we can reverse this bias with a simple intervention that boosts accuracy by nearly 10%.
