The goal of text-to-text generation is to make machines express like a human in many
applications such as conversation, summarization, and translation. It is one of the most …

There is a resurgent interest in developing intelligent open-domain dialog systems due to
the availability of large amounts of conversational data and the recent progress on neural …

We study knowledge-grounded dialogue generation with pre-trained language models. To
leverage the redundant external knowledge under capacity constraint, we propose …

Dialogue systems powered by large pre-trained language models (LM) exhibit an innate
ability to deliver fluent and natural-looking responses. Despite their impressive generation …

The research of knowledge-driven conversational systems is largely limited due to the lack
of dialog data which consist of multi-turn conversations on multiple topics and with …

While neural conversation models have shown great potentials towards generating
informative and engaging responses via introducing external knowledge, learning such a …

Knowledge-grounded dialogue systems are challenging to build due to the lack of training
data and heterogeneous knowledge sources. Existing systems perform poorly on unseen …

Responding with multi-modal content has been recognized as an essential capability for an
intelligent conversational agent. In this paper, we introduce the MMDialog dataset to better …

Recent years have witnessed a surge of interest in the field of open-domain dialogue.
Thanks to the rapid development of social media, large dialogue corpus from the Internet …

Human–computer conversation has long been an interest of artificial intelligence and
natural language processing research. Recent years have seen a dramatic improvement in …