Equation 6 · How a Model Actually Gets Small Enough to Run on a Phone
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Symbol T
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At T=1 this is the ordinary softmax used for prediction. Raising T flattens the distribution, pulling the small probabilities assigned to wrong classes up toward visibility, which is exactly the dark knowledge the method wants to expose. The training objective blends two terms: ordinary cross-entropy against the true label, and a match between the student’s and teacher’s temperature-softened distributions, measured by KL divergence:
Sources cited in the article section
- [1] Distilling the Knowledge in a Neural Network ↗
- [14] A Survey on Knowledge Distillation of Large Language Models ↗
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