Review for NeurIPS paper: CompRess: Self-Supervised Learning by Compressing Representations

This paper presents an approach for distillation of self-supervised models. All the reviewers acknowledge that the paper present a simple approach which outperforms several baselines. There are some concerns with respect to: (a) speed with which SSL field changes and applicability to new approaches; (b) clarity of tables; (c) claim of better than alexNet supervised. There was a rebuttal which answered some of the concerns. The AC agrees with authors that we should not wait for better models before working on model compression.