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LLM agents can achieve high task accuracy while exhibiting profound epistemic *im*humility, failing to acknowledge uncertainty even when presented with contradictory evidence.
BioKD achieves a remarkable 68.01% accuracy in trial-wise arousal recognition, showcasing the power of reliability-aware knowledge distillation in emotion recognition tasks.
Even when key ECG leads or segments are missing, SCAR enables robust zero-shot diagnosis by forcing models to compensate for lost information using secondary morphological cues.
MLLMs struggle with visually rendered text not because they can't reason, but because they can't *read* it, and a simple self-distillation fix closes the gap.
