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 …

A knowledge graph (KG), a special form of semantic network, integrates fragmentary data
into a graph to support knowledge processing and reasoning. KG quality control is important …

Emotion recognition in conversation (ERC) has promising potential in many fields, such as
recommendation systems, man–machine interaction, and medical care. In contrast to other …

As conversational AI-based dialogue management has increasingly become a trending
topic, the need for a standardized and reliable evaluation procedure grows even more …

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

Mixed-initiative dialogue tasks involve repeated exchanges of information and
conversational control. Conversational agents gain control by generating responses that …

Large language models can produce fluent dialogue but often hallucinate factual
inaccuracies. While retrieval-augmented models help alleviate this issue, they still face a …

Traditional conversational systems can only access the given query during the response
generation, leading to meaningless responses. To this end, researchers proposed to …

Despite achieving remarkable performance, previous knowledge-enhanced works usually
only use a single-source homogeneous knowledge base of limited knowledge coverage …

Abstract Knowledge-grounded dialogue generation has achieved promising performance
with the engagement of external knowledge sources. Typical approaches towards this task …