A humanized dialogue system is expected to generate empathetic replies, which should be
sensitive to the users' expressed emotion. The task of empathetic dialogue generation is …

In multi-turn dialogue generation, response is usually related with only a few contexts.
Therefore, an ideal model should be able to detect these relevant contexts and produce a …

Conversational systems have recently garnered increased attention due to advancements in
Large Language Models (LLMs) and Language Models for Dialogue Applications (LaMDA) …

The dominant framework of this article comes from the “Transactive Relationship Theory of
Nursing”/TRETON by Tanioka (16) articulating the relationship between human agent (the …

Recent years the task of incomplete utterance rewriting has raised a large attention.
Previous works usually shape it as a machine translation task and employ sequence to …

With the rapid progress of deep neural models and the explosion of available data
resources, dialogue systems that supports extensive topics and chit-chat conversations are …

Incorporating topic information can help response generation models to produce informative
responses for chat-bots. Previous work only considers the individual semantic of each topic …

Recently, knowledge-grounded conversations in the open domain gain great attention from
researchers. Existing works on retrieval-based dialogue systems have paid tremendous …

Topic drift is a common phenomenon in multi-turn dialogue. Therefore, an ideal dialogue
generation models should be able to capture the topic information of each context, detect the …

Multi-turn conversations consist of complex semantic structures, and it is still a challenge to
generate coherent and diverse responses given previous utterances. It's practical that a …