2 citations · 7 across the 5 of their papers we have counts for
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cs.CL2019★ 2 cited
DialogAct2Vec: Towards End-to-End Dialogue Agent by Multi-Task Representation Learning
Zhuoxuan Jiang, Ziming Huang, Dong Sheng Li +1
In end-to-end dialogue modeling and agent learning, it is important to (1) effectively learn knowledge from data, and (2) fully utilize heterogeneous information, e.g., dialogue ac…
cs.CL2019★ 2 cited
Towards End-to-End Learning for Efficient Dialogue Agent by Modeling Looking-ahead Ability
Zhuoxuan Jiang, Xian-Ling Mao, Ziming Huang +2
Learning an efficient manager of dialogue agent from data with little manual intervention is important, especially for goal-oriented dialogues. However, existing methods either tak…