Huang H.-H.Chen H.-H.2019-07-102019-07-102018978099924112710450823https://scholars.lib.ntu.edu.tw/handle/123456789/41307927th International Joint Conference on Artificial Intelligence, IJCAI 2018, 13 July 2018 through 19 July 2018This work demonstrates a writing assistant system that provides high level advice for Chinese scientific writing. Cross-lingual approaches are investigated to analyze the information structure of a given Chinese abstract and retrieve useful knowledge in the related work written in both English and Chinese. To the best of our knowledge, this is the first study on Chinese information structure identification. Without the need of labeled Chinese data, our novel model is capable of dealing with Chinese instances by acquiring language-invariant knowledge from the labeled English data. Adversarial learning is employed to enhance the cross-lingual sentence representation. ? 2018 International Joint Conferences on Artificial Intelligence.All right reserved.conference paper2-s2.0-85055713855https://www.scopus.com/inward/record.uri?eid=2-s2.0-85055713855&partnerID=40&md5=e12b2a795b68d2c7a8e63e28fe525e27