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Feature migration in Vision Transformers is predominantly an early-stage phenomenon, with deeper layers stabilizing faster than shallow ones.
Two heads are better than one: combining verbalized confidence and self-consistency with just two samples dramatically boosts uncertainty estimation in reasoning models, beating either signal alone even with much larger sampling budgets.
