Dictionary-Guided Editing Networks for Paraphrase Generation
Table 1: Results on MSCOCO dataset. Higher BLEU and METEOR score is better. Scores of the methods marked with * are taken from [Gupta et al.2017].
['[BOLD] Model', '[BOLD] Beam size', '[BOLD] BLEU', '[BOLD] METEOR']
The results demonstrate that our model consistently improves performance over other models for both greedy search and beam search. We get further improvement in both metrics though beam search, though, these improvements are not as significant as for Seq2Seq. This could be because the paraphrased dictionary provides some information for generating paraphrases, which could avoid our model to output the paraphrases which have only a few common terms. For MSCOCO, the comparison between two models is significant at 95% CI, if the difference in their score is more than 0.2 in BLEU and 0.1 in METEOR.