89 citations · 129 across the 5 of their papers we have counts for
5 papers
Cross-domain Dialogue Policy Transfer via Simultaneous Speech-act and Slot Alignment
Kaixiang Mo, Yu Zhang, Qiang Yang +1
Dialogue policy transfer enables us to build dialogue policies in a target domain with little data by leveraging knowledge from a source domain with plenty of data. Dialogue senten…
Fine Grained Knowledge Transfer for Personalized Task-oriented Dialogue Systems
Kaixiang Mo, Yu Zhang, Qiang Yang +1
Training a personalized dialogue system requires a lot of data, and the data collected for a single user is usually insufficient. One common practice for this problem is to share t…
Integrating User and Agent Models: A Deep Task-Oriented Dialogue System
Weiyan Wang, Yuxiang WU, Yu Zhang +3
Task-oriented dialogue systems can efficiently serve a large number of customers and relieve people from tedious works. However, existing task-oriented dialogue systems depend on h…
Flexible End-to-End Dialogue System for Knowledge Grounded Conversation
Wenya Zhu, Kaixiang Mo, Yu Zhang +3
In knowledge grounded conversation, domain knowledge plays an important role in a special domain such as Music. The response of knowledge grounded conversation might contain multip…
Personalizing a Dialogue System with Transfer Reinforcement Learning
Kaixiang Mo, Shuangyin Li, Yu Zhang +2
It is difficult to train a personalized task-oriented dialogue system because the data collected from each individual is often insufficient. Personalized dialogue systems trained o…