The integration of emotional support into various conversational scenarios presents
profound societal benefits, such as social interactions, mental health counseling, and …

Dialogue systems are designed to offer human users social support or functional services
through natural language interactions. Traditional conversation research has put significant …

Conversational agents, or commonly known as dialogue systems, have gained escalating
popularity in recent years. Their widespread applications support conversational interactions …

Generating fluent and informative natural responses while main-taining representative
internal states for search optimization is critical for conversational search systems. Existing …

Dynamic graph modeling is crucial for understanding complex structures in web graphs,
spanning applications in social networks, recommender systems, and more. Most existing …

Spoken dialogue systems (SDS) heavily rely on dialogue state tracking (DST) for success.
However, providing sufficient computational power for training proves challenging, given …

Discovering new slots is critical to the success of dialogue systems. Most existing methods
rely on automatic slot induction in unsupervised fashion or perform domain adaptation …

Conversation disentanglement aims to group utterances into detached sessions, which is a
fundamental task in processing multi-party conversations. Existing methods have two main …

Existing multimodal conversation agents have shown impressive abilities to locate absolute
positions or retrieve attributes in simple scenarios, but they fail to perform well when …

Within Dialogue Modeling research in AI and NLP, considerable attention has been spent
on``dialogue state tracking''(DST), which is the ability to update the representations of the …