This repository aggregates foundational and recent research papers on Knowledge Distillation, covering techniques where smaller student models learn from larger teacher models. It includes seminal works by Geoffrey Hinton, Yoshua Bengio, and other researchers, spanning topics like dark knowledge, model compression, and transfer learning. The collection serves as a reference for ML practitioners and researchers studying model efficiency and knowledge transfer.