SAD-LoRA: Spectral Alignment for Low-Rank Knowledge Distillation
SAD-LoRA is proposed (SAD-LoRA), which selects this subspace from the data-weighted student-space reference update $\DWT\Sigx^{1/2}$ and maintains it during training via a differentiable principal-angle loss on $\colspan(B)$.