Despite showing increasingly human-like conversational abilities, state-of-the-art dialogue
models often suffer from factual incorrectness and hallucination of knowledge (Roller et al …

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 …

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

Collecting high quality conversational data can be very expensive for most applications and
infeasible for others due to privacy, ethical, or similar concerns. A promising direction to …

Maintaining consistent personas is essential for dialogue agents. Although tremendous
advancements have been brought, the limited-scale of annotated persona-dense data are …

Recently, the advent of large language models (LLMs) has revolutionized generative
agents. Among them, Role-Playing Conversational Agents (RPCAs) attract considerable …

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 …

Multi-party conversations (MPCs) are a more practical and challenging scenario involving
more than two interlocutors. This research topic has drawn significant attention from both …

In recent years, with the development of deep learning, text-generation technology has
undergone great changes and provided many kinds of services for human beings, such as …

Training grounded response generation models often requires a large collection of
grounded dialogues. However, it is costly to build such dialogues. In this paper, we present …