Review for NeurIPS paper: LoCo: Local Contrastive Representation Learning

Weaknesses: The paper claims in the Abstract that "by overlapping local blocks" (i.e. the first proposed method), it "closes the performance gap between local learning and end-to-end contrastive learning algorithms for the first time." However, the presented empirical results can not support the claim. The comparisons with baseline SimCLR in Table-1 are not fair. SimCLR can achieve accuracy of 65.7% without extra layers in the decoder and 67.1% with extra layers according to Table-4. However, Table-1 is comparing SimCLR without extra layers versus the proposed solution with extra layers.