Reproduce “Progressive$^2$: A Teacher-Student Progressive Co-Evolving Knowledge Distillation Method for Substantial Model Compression” on OpenResearch

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About this paper

Tiancong Cheng, Ying Zhang, Zhiwen Yu, Yifang Yin, Bin Guo

Progressive² distillation transfers knowledge from a large teacher to a compact student by introducing deeper teacher features in stages, with an optional sequence of progressively smaller students. On Cityscapes, its 1.57-million-parameter student reports 58.39% mIoU and 92.88% pixel accuracy, versus 55.68% and 91.91% for TAKD+DIST. The proposed mechanism is not established as causal.

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