Emotion detection in dialogues is challenging as it often requires the identification of
thematic topics underlying a conversation, the relevant commonsense knowledge, and the …

Current approaches to empathetic response generation focus on learning a model to predict
an emotion label and generate a response based on this label and have achieved …

Abnormal crowd behavior detection has recently attracted increasing attention due to its
wide applications in computer vision research areas. However, it is still an extremely …

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 …

Structured belief states are crucial for user goal tracking and database query in task-oriented
dialog systems. However, training belief trackers often requires expensive turn-level …

Poetry generation, and creative language generation in general, usually suffers from the
lack of large training data. In this paper, we present a novel framework to generate sonnets …

Insufficient semantic understanding of dialogue always leads to the appearance of generic
responses, in generative dialogue systems. Recently, highquality knowledge bases have …

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 …

Learning discrete dialog structure graph from human-human dialogs yields basic insights
into the structure of conversation, and also provides background knowledge to facilitate …