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20162026
most citedRethinking Action Spaces for Reinforcement Learning in End-to-end Dialog Agents with Latent Variable Models

22 citations · 110 across the 26 of their papers we have counts for

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Showing 2017Show all

2 papers · 1 filter

cs.CL2017★ 13 cited

Generative Encoder-Decoder Models for Task-Oriented Spoken Dialog Systems with Chatting Capability

Tiancheng Zhao, Allen Lu, Kyusong Lee +1

Generative encoder-decoder models offer great promise in developing domain-general dialog systems. However, they have mainly been applied to open-domain conversations. This paper p…

cs.CL2017

Learning Discourse-level Diversity for Neural Dialog Models using Conditional Variational Autoencoders

Tiancheng Zhao, Ran Zhao, Maxine Eskenazi

While recent neural encoder-decoder models have shown great promise in modeling open-domain conversations, they often generate dull and generic responses. Unlike past work that has…