A smaller distilled LLM may beat its teacher by being forced to generalize
peterjliu · x · 2026-07-25
The poster argues that if the largest LLMs are over-parameterized, distillation may produce a student that outperforms the teacher. The reasoning is that very large models may benefit from memorizing more facts, while a smaller student forced to match performance with less capacity may generalize better.
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