no code implementations • ICLR 2019 • Yaohua Tang, Kaixiang Mo, Qian Xu, Chao Zhang, Qiang Yang
When building models for novel natural language domains, a major challenge is the lack of data in the new domains, no matter whether the data is annotated or not.
no code implementations • 20 Apr 2018 • Kaixiang Mo, Yu Zhang, Qiang Yang, Pascale Fung
Also, they depend on either common slots or slot entropy, which are not available when the source and target slots are totally disjoint and no database is available to calculate the slot entropy.
no code implementations • 11 Nov 2017 • Kaixiang Mo, Yu Zhang, Qiang Yang, Pascale Fung
Training a personalized dialogue system requires a lot of data, and the data collected for a single user is usually insufficient.
no code implementations • 10 Nov 2017 • Weiyan Wang, Yuxiang Wu, Yu Zhang, Zhongqi Lu, Kaixiang Mo, Qiang Yang
Then the built user model is used as a leverage to train the agent model by deep reinforcement learning.
no code implementations • 13 Sep 2017 • Wenya Zhu, Kaixiang Mo, Yu Zhang, Zhangbin Zhu, Xuezheng Peng, Qiang Yang
Although existing generative question answering (QA) systems can be applied to knowledge grounded conversation, they either have at most one entity in a response or cannot deal with out-of-vocabulary entities.
no code implementations • 10 Oct 2016 • Kaixiang Mo, Shuangyin Li, Yu Zhang, Jiajun Li, Qiang Yang
One way to solve this problem is to consider a collection of multiple users' data as a source domain and an individual user's data as a target domain, and to perform a transfer learning from the source to the target domain.