%0 Conference Proceedings %T Generating Syntactic Paraphrases %A Colin, Emilie %A Gardent, Claire %Y Riloff, Ellen %Y Chiang, David %Y Hockenmaier, Julia %Y Tsujii, Jun’ichi %S Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing %D 2018 %8 oct nov %I Association for Computational Linguistics %C Brussels, Belgium %F colin-gardent-2018-generating %X We study the automatic generation of syntactic paraphrases using four different models for generation: data-to-text generation, text-to-text generation, text reduction and text expansion, We derive training data for each of these tasks from the WebNLG dataset and we show (i) that conditioning generation on syntactic constraints effectively permits the generation of syntactically distinct paraphrases for the same input and (ii) that exploiting different types of input (data, text or data+text) further increases the number of distinct paraphrases that can be generated for a given input. %R 10.18653/v1/D18-1113 %U https://aclanthology.org/D18-1113 %U https://doi.org/10.18653/v1/D18-1113 %P 937-943