… A general teacher–student framework for knowledge distillation is shown in Fig. 1. … different
categories of knowledge for knowledge distillation. A vanilla knowledge distillation uses the …

… is to form a better teacher model from the student without additional … In such a situation,
the knowledge from the input … This paper is about knowledge distillation (KD) and studentteacher …

… network and a pre-trained large one as a teacher, both fixed and (wrongly) presumed to …
we propose a new distillation framework called Teacher Assistant Knowledge Distillation (TAKD)…

Knowledge distillation (KD) is a new method for transferring knowledge of a structure under …
small model (named as a student) by soft labels produced by a complex model (named as a …

… teachers often don’t make good teachers, we attempt to tease apart the factors that affect
knowledge distillation … We find crucially that larger models do not often make better teachers. …

… settings, where the teacher models and training … distill better from a stronger teacher. We
empirically find that the discrepancy of predictions between the student and a stronger teacher …

… knowledge distillation using teacher student training for building accurate and compact neural
networks. We show that with knowledge … multiple teacher labels for training student models…

… In this paper, we present a simple knowledge distillation technique and demonstrate that it
… between teacher and student models with no need for elaborate knowledge representations. …

… teachers do not make better students due to the capacity mismatch. To this end, we present
a novel adaptive knowledge distillation … as Student Customized Knowledge Distillation (…

… knowledge distillation approach to facilitate the transfer of dark knowledge from a teacher to
a student. … effective training of student models given pretrained teachers, we aim to learn the …