Review for NeurIPS paper: Hard Negative Mixing for Contrastive Learning

Weaknesses: In general, my biggest concern is that the efficacy of the proposed method is not very significant. For example, can the proposed module directly be dropped in to improve [25] and [28]? In line 233-234, the explanation here is a bit counter-intuitive. I understand this is possible if inter-class distance increases more than intra-class variance, but can you plot it to justify it better? Otherwise, increasing intra-class variance should lead to lower accuracy.