255 citations · 1.3k across the 24 of their papers we have counts for
8 papers · 1 filter
DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generation
Yizhe Zhang, Siqi Sun, Michel Galley +6
We present a large, tunable neural conversational response generation model, DialoGPT (dialogue generative pre-trained transformer). Trained on 147M conversation-like exchanges ext…
Generating a Common Question from Multiple Documents using Multi-source Encoder-Decoder Models
Woon Sang Cho, Yizhe Zhang, Sudha Rao +2
Ambiguous user queries in search engines result in the retrieval of documents that often span multiple topics. One potential solution is for the search engine to generate multiple…
Structuring Latent Spaces for Stylized Response Generation
Xiang Gao, Yizhe Zhang, Sungjin Lee +4
Generating responses in a targeted style is a useful yet challenging task, especially in the absence of parallel data. With limited data, existing methods tend to generate response…
Domain Adaptive Text Style Transfer
Dianqi Li, Yizhe Zhang, Zhe Gan +4
Text style transfer without parallel data has achieved some practical success. However, in the scenario where less data is available, these methods may yield poor performance. In t…
Conversing by Reading: Contentful Neural Conversation with On-demand Machine Reading
Lianhui Qin, Michel Galley, Chris Brockett +5
Although neural conversation models are effective in learning how to produce fluent responses, their primary challenge lies in knowing what to say to make the conversation contentf…
Jointly Optimizing Diversity and Relevance in Neural Response Generation
Xiang Gao, Sungjin Lee, Yizhe Zhang +4
Although recent neural conversation models have shown great potential, they often generate bland and generic responses. While various approaches have been explored to diversify the…
Consistent Dialogue Generation with Self-supervised Feature Learning
Yizhe Zhang, Xiang Gao, Sungjin Lee +4
Generating responses that are consistent with the dialogue context is one of the central challenges in building engaging conversational agents. We demonstrate that neural conversat…
Dialog System Technology Challenge 7
Koichiro Yoshino, Chiori Hori, Julien Perez +14
This paper introduces the Seventh Dialog System Technology Challenges (DSTC), which use shared datasets to explore the problem of building dialog systems. Recently, end-to-end dial…