Sequential Copying Networks
Table 1: Full length Rouge F1 evaluation results on the English Gigaword test set used by rush-chopra-weston:2015:EMNLP rush-chopra-weston:2015:EMNLP. RG in the Table denotes Rouge. Results with ‡ mark are taken from the corresponding papers.
['[BOLD] Models', '[BOLD] RG-1', '[BOLD] RG-2', '[BOLD] RG-L']
EMNLP test set, \citeauthorzhou-EtAl:2017: Long \shortcitezhou-EtAl:2017: Long test set and our internal test set. As indicated in these tables, SeqCopyNet performs better than all the baseline models. As previously mentioned, the performance of copying methods performs comparably to the s2s+att baseline on test sets of \citeauthorrush-chopra-weston:2015: EMNLP \shortciterush-chopra-weston:2015: EMNLP and \citeauthorzhou-EtAl:2017:Long \shortcitezhou-EtAl:2017: Long, since the rare words and numbers have already been replaced in the references.