Before revision:  Our experiments on the WMT19 metrics tasks for all into-English language directions show that somewhat surprisingly, the addition of diverse paraphrases, even those produced by humans, leads to only small, inconsistent changes in BLEU's correlation with human judgments, suggesting that BLEU's ability to correctly exploit multiple references is limited
After revision:  Our experiments on the WMT19 metrics tasks for all into-English language directions of the WMT19 metrics task (at both the system and sentence level) show that using paraphrased references does generally improve BLEU, and when it does, the more diverse the better. However, we also show that better results could be achieved if those paraphrases were to specifically target the parts of the space most relevant to the MT outputs being evaluated. Moreover, the gains remain slight even when human paraphrases are used, suggesting inherent limitations to BLEU's ability to correctly exploit multiple references is limited