Park et al. investigated the field of polysomnography, which is used for sleep staging, but is tedious to perform due to the numerous instruments needed. They developed DistillSleep, which is a system that uses a single-channel electroencephalogram, or EEG, to perform sleep staging using less resource-intensive devices. It used two models, a high-capacity teacher model, and a 109 k-parameter student model, which both used a Multi-Wavelength Pyramid module and Transformer structure to acquire intra- and inter- epoch contexts. The knowledge transfer from the teacher to the student was performed using feature- and prediction- type distillations. The training of the teacher models was performed using over 10,000 overnight recordings, and the performance of the models was evaluated using Macro-F1. The teacher and student models were able to perform extremely well under the Macro-F1 evaluation scale, with the student earning an accuracy level up to 79.7%.