244 citations · 245 across the 11 of their papers we have counts for
4 papers · 1 filter
Towards Efficient Dialogue Pre-training with Transferable and Interpretable Latent Structure
Xueliang Zhao, Lemao Liu, Tingchen Fu +3
With the availability of massive general-domain dialogue data, pre-trained dialogue generation appears to be super appealing to transfer knowledge from the general domain to downst…
There Is No Standard Answer: Knowledge-Grounded Dialogue Generation with Adversarial Activated Multi-Reference Learning
Xueliang Zhao, Tingchen Fu, Chongyang Tao +1
Knowledge-grounded conversation (KGC) shows excellent potential to deliver an engaging and informative response. However, existing approaches emphasize selecting one golden knowled…
Learning to Express in Knowledge-Grounded Conversation
Xueliang Zhao, Tingchen Fu, Chongyang Tao +3
Grounding dialogue generation by extra knowledge has shown great potentials towards building a system capable of replying with knowledgeable and engaging responses. Existing studie…
There Are a Thousand Hamlets in a Thousand People's Eyes: Enhancing Knowledge-grounded Dialogue with Personal Memory
Tingchen Fu, Xueliang Zhao, Chongyang Tao +2
Knowledge-grounded conversation (KGC) shows great potential in building an engaging and knowledgeable chatbot, and knowledge selection is a key ingredient in it. However, previous…