How does Naïve Bayes integrate into probabilistic knowledge distillation pipelines?

Naïve Bayes can act as a teacher or student model in knowledge distillation by transferring probabilistic outputs.

In distillation, a complex teacher model provides soft labels. Naïve Bayes can either learn from these distributions or serve as a lightweight baseline teacher. Its probabilistic outputs are well-suited for KL-divergence-based distillation objectives, especially in low-resource environments.