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20172020
most citedFlexible End-to-End Dialogue System for Knowledge Grounded Conversation

89 citations · 115 across the 5 of their papers we have counts for

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Showing cs.CLShow all

6 papers · 1 filter

cs.CL2019

Transferable End-to-End Aspect-based Sentiment Analysis with Selective Adversarial Learning

Zheng Li, Xin Li, Ying Wei +3

Joint extraction of aspects and sentiments can be effectively formulated as a sequence labeling problem. However, such formulation hinders the effectiveness of supervised methods d…

cs.CL2018

Exploiting Coarse-to-Fine Task Transfer for Aspect-level Sentiment Classification

Zheng Li, Ying Wei, Yu Zhang +3

Aspect-level sentiment classification (ASC) aims at identifying sentiment polarities towards aspects in a sentence, where the aspect can behave as a general Aspect Category (AC) or…

cs.CL2018

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…

cs.CL201714 cited

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…

cs.CL2017

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…

cs.CL201789 cited

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…