Review for NeurIPS paper: Movement Pruning: Adaptive Sparsity by Fine-Tuning

Additional Feedback: - For the results in Figure 2, what does the x-axis represent for models with different numbers of parameters? For example, if a MiniBERT model has half as many parameters as BERT-base, then comparing "10% remaining weights" seems a bit unfair. What would the figure look like if the x-axis were instead the number of non-zero parameters? - You evaluate on one span extraction and two paired sentence classification tasks, but no single sentence classification tasks. Why not replace one of the sentence pair tasks with SST-2, for example? I expect the results would be similar, but it would make the experiments a bit more compelling.