A Statistical Perspective on Knowledge Distillation: Foundations, Classical Methods, and Large Language Model Extensions

Knowledge Distillation (KD) has emerged as a vital paradigm for transferring the capabilities of high-capacity models to efficient ``student'' counterparts, addressing critical challenges in computational cost, deployment constraints, and privacy-sensitive settings. Although KD is widely used in pra